{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 概述\n",
    "\n",
    "欢迎访问我的个人Github查看更多内容（国内访问Github可能存在问题，可以换个时间段访问，或者百度解决方案）： https://github.com/charliedream1/ai_quant_trade\n",
    "\n",
    "本文采用了聚宽因子库共260个因子作为示例（由于数据接口存在访问量限制，下文示例仅使用了60个因子，并挑选了15值股票，半年的时间作为训练数据，演示整个流程）。\n",
    "\n",
    "聚宽因子库，共260个因子：https://www.joinquant.com/help/api/help#name:factor_values\n",
    "\n",
    "本文主要讲解采用260因子，以及lightGBM模型，采用TopKDropN策略选股调仓的详细流程和分析过程。策略主要流程如下：   \n",
    "* 将时间拆分为训练/验证/测试三个时间段，使用聚宽260因子库，获取股票因子，数据维度是T*D(T即时间1维，D是因子维度)\n",
    "* 使用LightGBM进行训练，并进行预测\n",
    "* 对“涨”概率值排序，选择TopK的股票。对持仓股票预测，“跌”的概率排序，做空N个股票"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1. 机器学习/深度学习训练总结\n",
    "\n",
    "## 1.1 常见训练数据使用方式；    \n",
    "1.使用基础数据，通过技术指标统计多天，将时间维度压成1维（如5日均值，将5日统计为1日），即1支股票是一个（1*N）维度的特征,\n",
    "  1为时间，N为特征的维度    \n",
    "2.采用滑动窗口，保留时间维，即1支股票是一个（T*N）维度的特征   \n",
    "\n",
    "\n",
    "## 1.2 特征选择     \n",
    "不同周期，不同因子的重要性不同，因此，特征选择主要有一下方案：        \n",
    "1.采用尽可能多的因子，因子不变，固定周期重训模型，以保持模型的稳定     \n",
    "2.固定周期，根据因子权重，重选因子后，重训模型   \n",
    "\n",
    "特征处理：    \n",
    "1. 去极值，标准化，归一化\n",
    "2. nan值剔除，或用0/均值填充\n",
    "3. 通过模型进行因子权重打分进行选择\n",
    "4. 通过特征降维算法压缩\n",
    "\n",
    "\n",
    "## 1.3 训练和验证数据拆分流程 （优选方案1或2）             \n",
    "1.按时间段，比如2018年为训练，2019年为验证集，2020做测试集     \n",
    "2.比如2018年等分切分为12分，奇数作训练，偶数做验证，2019做测试机     \n",
    "3.对训练集直接打散后，7：3拆分为训练和验证集，小概率情况下出现行情好的都分到了训练集，\n",
    "  行情差的都在验证集，可能导致训练的不好。\n",
    "\n",
    "\n",
    "## 1.4 标签制作和使用\n",
    "1.回归类标签：即使用实际股票价值，或者涨跌幅作为预测值，但往往误差较大，可能预测不准，虽然分析过程，\n",
    "  通过绘图，可以看到预测趋势和真实值很接近，但实际误差仍然很大\n",
    "2.分类标签：相对回归会更加准确，但是需要大量的尝试以及精细分类，比如最简单的分类，就是预测涨还是跌，\n",
    "  如果分类详细一些，则是按涨跌幅度分为几类，进行预测。得到预测结果后，可以按照打分进行排序后选股。\n",
    "\n",
    "\n",
    "## 1.5 回测中可能存在的问题     \n",
    "### 1.5.1 模拟和真实的差异\n",
    "回测和真是交易存在一定的差异，因此，只可能尽可能接近实际的模拟，但和真实存在一定差异，如：    \n",
    "1.概率性买入失败：真实交易可能存在涨跌停导致没有买入或卖出，而回测无法很好的模拟    \n",
    "2.滑点：由于价格快速实时波动，导致下单和实际成交价格存在差异，回测往往采用一个固定比率模拟    \n",
    "3.交易值：回测往往采取一天的收盘价或者平均价作为交易价格，与实际存在差异\n",
    "\n",
    "### 1.5.2 注意事项\n",
    "需注意引入未来 （深度学习中Attention网络注意对未来进行mask,其余模型对日期进行平移）\n",
    "\n",
    "### 1.5.3 测试流程\n",
    "如果回测周期很长，比如8年，那么行情好的期间可能掩盖行情不好期间的亏损问题。\n",
    "因此，建议对牛市/熊市/长周期（比如连续2年+），之后对近期模拟交易跟踪，综合评定后，\n",
    "如果策略Okay，则上线使用。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2. 待调试超参数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 通过同花顺，查看上证指数，月线，挑选时间段\n",
    "# 市场行情很好（大盘指数约从2118-4611点）：2014-4-30: 2015-5-30\n",
    "# 市场行情较好 (大盘指数约从2807-3497点) 2020-04-30：2021-11-30 \n",
    "# 市场行情不好 (大盘指数约从3413-2618) 2018-1-30: 2019-1-31 \n",
    "market_pool = '000300.XSHG'  # 沪深300\n",
    "train = ['2020-06-30', '2020-12-30']\n",
    "eval = ['2021-01-01', '2021-02-20']\n",
    "test = ['2021-03-31', '2021-05-30']\n",
    "\n",
    "market_pool = '000300.XSHG'  # 用沪深300作为选股股票池\n",
    "view_len = 20  # 滑动窗口查看的天数\n",
    "stk_num = 10 # 数据量大运算事件过长，暂时只选择15个\n",
    "factor_num = 60  # 因子使用的数量，数据量大运算事件过长，暂时只选择80个"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3. 数据准备\n",
    "## 3.1 获取股票列表"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total Num: 15\n",
      "['000001.XSHE', '000002.XSHE', '000063.XSHE', '000066.XSHE', '000069.XSHE', '000100.XSHE', '000157.XSHE', '000166.XSHE', '000301.XSHE', '000333.XSHE']\n"
     ]
    }
   ],
   "source": [
    "from jqlib.technical_analysis import *\n",
    "from jqdata import *\n",
    "\n",
    "# 获取沪深300股票列表\n",
    "hs300_stock_lst = get_index_stocks(market_pool)\n",
    "hs300_stock_lst = hs300_stock_lst[:stk_num]\n",
    "print('Total Num:', len(hs300_stock_lst))\n",
    "print(hs300_stock_lst[:10])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.2 获取股票数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>close</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>volume</th>\n",
       "      <th>money</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-06-30</th>\n",
       "      <td>12.50</td>\n",
       "      <td>12.48</td>\n",
       "      <td>12.55</td>\n",
       "      <td>12.40</td>\n",
       "      <td>96232862.0</td>\n",
       "      <td>1.199182e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-01</th>\n",
       "      <td>12.47</td>\n",
       "      <td>12.79</td>\n",
       "      <td>12.82</td>\n",
       "      <td>12.42</td>\n",
       "      <td>174152569.0</td>\n",
       "      <td>2.202801e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-02</th>\n",
       "      <td>12.75</td>\n",
       "      <td>13.09</td>\n",
       "      <td>13.15</td>\n",
       "      <td>12.64</td>\n",
       "      <td>265785962.0</td>\n",
       "      <td>3.433511e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-03</th>\n",
       "      <td>13.23</td>\n",
       "      <td>13.89</td>\n",
       "      <td>13.96</td>\n",
       "      <td>13.22</td>\n",
       "      <td>386631816.0</td>\n",
       "      <td>5.280918e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-06</th>\n",
       "      <td>14.23</td>\n",
       "      <td>15.28</td>\n",
       "      <td>15.28</td>\n",
       "      <td>14.22</td>\n",
       "      <td>483396858.0</td>\n",
       "      <td>7.168653e+09</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             open  close   high    low       volume         money\n",
       "2020-06-30  12.50  12.48  12.55  12.40   96232862.0  1.199182e+09\n",
       "2020-07-01  12.47  12.79  12.82  12.42  174152569.0  2.202801e+09\n",
       "2020-07-02  12.75  13.09  13.15  12.64  265785962.0  3.433511e+09\n",
       "2020-07-03  13.23  13.89  13.96  13.22  386631816.0  5.280918e+09\n",
       "2020-07-06  14.23  15.28  15.28  14.22  483396858.0  7.168653e+09"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# get_price 取多只股票数据时, 为了对齐日期, 不能跳过停牌\n",
    "# todo:考虑每支股票分开处理，过滤停牌的日期\n",
    "# 获取一支或者多只股票的行情数据, 按天或者按分钟，这里在使用时注意 end_date 的设置，\n",
    "#   传入的值不要大于context.current_dt，否则会引入未来函数。\n",
    "# 关于停牌: 因为此API可以获取多只股票的数据, 可能有的股票停牌有的没有, 为了保持时间轴的一致\n",
    "# panel将在pandas未来版本不再支持，将来升级pandas后，您的策略会失败\n",
    "#df = get_price(hs300_stock_lst, start_date=train[0], end_date=train[1], \n",
    "#               frequency='daily', skip_paused=False, fill_paused=True, panel=True)\n",
    "\n",
    "# 最好并行获取单只股票信息\n",
    "df = get_price(hs300_stock_lst[0], start_date=train[0], end_date=train[1], \n",
    "               frequency='daily', skip_paused=False, fill_paused=True, panel=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.3 获取因子（聚宽260因子）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                       factor      ...       category_intro\n",
      "0  administration_expense_ttm      ...           基础科目及衍生类因子\n",
      "1   asset_impairment_loss_ttm      ...           基础科目及衍生类因子\n",
      "2    cash_flow_to_price_ratio      ...           基础科目及衍生类因子\n",
      "3      circulating_market_cap      ...           基础科目及衍生类因子\n",
      "4                        EBIT      ...           基础科目及衍生类因子\n",
      "\n",
      "[5 rows x 4 columns]\n",
      "Num:  260\n"
     ]
    }
   ],
   "source": [
    "#获取聚宽因子库所有因子\n",
    "from jqfactor import get_all_factors \n",
    "df_factors_info = get_all_factors()\n",
    "print(df_factors_info.head())\n",
    "print('Num: ', len(df_factors_info))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['administration_expense_ttm', 'asset_impairment_loss_ttm', 'cash_flow_to_price_ratio']\n"
     ]
    }
   ],
   "source": [
    "factor_lst = list(df_factors_info['factor'])[:factor_num]  # 只选择80个，选择太多，时间过长，而且有调用限制\n",
    "print(factor_lst[:3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>code</th>\n",
       "      <th>000001.XSHE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-06-30</th>\n",
       "      <td>79.321560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-01</th>\n",
       "      <td>99.755665</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-02</th>\n",
       "      <td>116.372405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-03</th>\n",
       "      <td>143.123404</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-06</th>\n",
       "      <td>180.262966</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "code        000001.XSHE\n",
       "2020-06-30    79.321560\n",
       "2020-07-01    99.755665\n",
       "2020-07-02   116.372405\n",
       "2020-07-03   143.123404\n",
       "2020-07-06   180.262966"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 导入函数库\n",
    "from jqfactor import get_factor_values\n",
    "\n",
    "# 为了防止单次返回数据时间过长，每次调用 api 请求的因子值不能超过 200000 个\n",
    "# 因子库中nan值：缺少依赖数据;财务数据中如果标的未披露相关字段,依赖数据不完整的话会返回nan值,请注意到财务报表披露规则变更,标的报表披露形式(金融类,非金融类等) , 以及标的上市时间等\n",
    "\n",
    "# 返回：\n",
    "# * 一个 dict： key 是因子名称， value 是 pandas.dataframe。\n",
    "# # dataframe 的 index 是日期， column 是股票代码， value 是因子值\n",
    "\n",
    "factor_data = get_factor_values(securities=['000001.XSHE'], factors=factor_lst, \n",
    "                                start_date=train[0], end_date=train[1])\n",
    "\n",
    "# 查看因子值\n",
    "factor_data['AR'].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 4. 模型数据准备\n",
    "注意：sklearn类模型不支持2D数据，即时间维度必须是1，每一行一个标签值\n",
    "## 4.1 分类模型数据准备\n",
    "### 4.1.1 实验测试"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-06-30   -0.02\n",
      "2020-07-01    0.32\n",
      "2020-07-02    0.34\n",
      "2020-07-03    0.66\n",
      "2020-07-06    1.05\n",
      "dtype: float64\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "pandas.core.series.Series"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 判断涨或者跌\n",
    "df_lab = df['close'] - df['open']\n",
    "print(df_lab.head())\n",
    "type(df_lab)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "value: [[12.47 12.79 12.82 12.42 174152569.0 2202800843.97]\n",
      " [12.75 13.09 13.15 12.64 265785962.0 3433511084.46]]\n",
      "shape: (20, 6)\n",
      "type <class 'numpy.ndarray'>\n"
     ]
    }
   ],
   "source": [
    "tmp = df.iloc[1: 1 + view_len, :].values\n",
    "print('value:', tmp[:2])\n",
    "print('shape:', tmp.shape)\n",
    "print('type', type(tmp))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([12.5, 12.48, 12.55])"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "arr = df.values\n",
    "arr[0, 0:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x [array([[12.47, 12.79, 12.82, 12.42, 174152569.0, 2202800843.97],\n",
      "       [12.75, 13.09, 13.15, 12.64, 265785962.0, 3433511084.46],\n",
      "       [13.23, 13.89, 13.96, 13.22, 386631816.0, 5280918011.4],\n",
      "       [14.23, 15.28, 15.28, 14.22, 483396858.0, 7168653356.25],\n",
      "       [15.89, 15.09, 16.21, 14.65, 406751085.0, 6267919683.04],\n",
      "       [14.84, 15.36, 15.59, 14.84, 269975946.0, 4095447757.17],\n",
      "       [15.26, 15.14, 15.26, 14.92, 230234293.0, 3469517329.73],\n",
      "       [14.96, 14.48, 15.09, 14.39, 221490586.0, 3254272377.89],\n",
      "       [14.33, 14.51, 14.7, 14.13, 198753032.0, 2871414844.76],\n",
      "       [14.52, 14.31, 14.81, 14.18, 200436306.0, 2891773817.07],\n",
      "       [14.41, 13.91, 14.48, 13.87, 209567372.0, 2947173149.72],\n",
      "       [13.94, 13.79, 14.18, 13.76, 198109849.0, 2771496391.19],\n",
      "       [13.81, 13.78, 13.92, 13.6, 132492448.0, 1821043927.51],\n",
      "       [13.87, 14.36, 14.4, 13.74, 203110656.0, 2872758056.19],\n",
      "       [14.31, 14.12, 14.31, 14.04, 128544281.0, 1815570300.6],\n",
      "       [14.12, 14.04, 14.28, 13.91, 134709107.0, 1895447229.41],\n",
      "       [13.88, 13.65, 13.93, 13.46, 208024577.0, 2838535210.75],\n",
      "       [13.62, 13.16, 13.64, 13.08, 187848857.0, 2504647111.34],\n",
      "       [13.32, 12.9, 13.33, 12.77, 192955426.0, 2497551472.28],\n",
      "       [13.0, 13.0, 13.09, 12.85, 124865068.0, 1618089558.6]])]\n",
      "y [1]\n"
     ]
    }
   ],
   "source": [
    "# 由于是3D数据，这种方式只适合深度学习模型使用\n",
    "import numpy as np\n",
    "x, y = [], []\n",
    "# -1用于错开数据和标签，避免引入未来\n",
    "for i in range(1, len(df) - view_len - 1):\n",
    "    ft = df.iloc[i: i + view_len, :].values\n",
    "    x.append(ft)\n",
    "    if df_lab[i+1] > 0:\n",
    "        y.append(1)\n",
    "    else:\n",
    "        y.append(0)\n",
    "\n",
    "print('x', x[:1])\n",
    "print('y', y[:1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(20, 6)"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x[1].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "Found array with dim 3. Estimator expected <= 2.",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-40-d100da4c9977>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0msvm\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mSVC\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkernel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'linear'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0msvm\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/sklearn/svm/base.py\u001b[0m in \u001b[0;36mfit\u001b[0;34m(self, X, y, sample_weight)\u001b[0m\n\u001b[1;32m    147\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_sparse\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msparse\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mcallable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkernel\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    148\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 149\u001b[0;31m         \u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcheck_X_y\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfloat64\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0morder\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'C'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maccept_sparse\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'csr'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    150\u001b[0m         \u001b[0my\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_validate_targets\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    151\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/sklearn/utils/validation.py\u001b[0m in \u001b[0;36mcheck_X_y\u001b[0;34m(X, y, accept_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, multi_output, ensure_min_samples, ensure_min_features, y_numeric, warn_on_dtype, estimator)\u001b[0m\n\u001b[1;32m    571\u001b[0m     X = check_array(X, accept_sparse, dtype, order, copy, force_all_finite,\n\u001b[1;32m    572\u001b[0m                     \u001b[0mensure_2d\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mallow_nd\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mensure_min_samples\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 573\u001b[0;31m                     ensure_min_features, warn_on_dtype, estimator)\n\u001b[0m\u001b[1;32m    574\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mmulti_output\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    575\u001b[0m         y = check_array(y, 'csr', force_all_finite=True, ensure_2d=False,\n",
      "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/sklearn/utils/validation.py\u001b[0m in \u001b[0;36mcheck_array\u001b[0;34m(array, accept_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, warn_on_dtype, estimator)\u001b[0m\n\u001b[1;32m    449\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mallow_nd\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0marray\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mndim\u001b[0m \u001b[0;34m>=\u001b[0m \u001b[0;36m3\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    450\u001b[0m             raise ValueError(\"Found array with dim %d. %s expected <= 2.\"\n\u001b[0;32m--> 451\u001b[0;31m                              % (array.ndim, estimator_name))\n\u001b[0m\u001b[1;32m    452\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mforce_all_finite\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    453\u001b[0m             \u001b[0m_assert_all_finite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: Found array with dim 3. Estimator expected <= 2."
     ]
    }
   ],
   "source": [
    "# 由于是3D数据，sklearn只支持2D数据，所以会报错\n",
    "from sklearn.svm import SVC\n",
    "\n",
    "svm = SVC(kernel='linear')\n",
    "svm.fit(x, y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 4.1.2 训练测试数据准备"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.ori: \n",
      "                  A       B       C\n",
      "1980-01-01  4.0405  1.7246  804.74\n",
      "1980-02-01  4.0963  1.7482  810.01\n",
      "1980-03-01  4.3149  1.8519  860.13\n",
      "1980-04-01  3.9860  1.8220  790.11\n",
      "2.add pct_chg:\n",
      "                  A       B       C       lab\n",
      "1980-01-01  4.0405  1.7246  804.74       NaN\n",
      "1980-02-01  4.0963  1.7482  810.01  0.006549\n",
      "1980-03-01  4.3149  1.8519  860.13  0.061876\n",
      "1980-04-01  3.9860  1.8220  790.11 -0.081406\n",
      "3.shift df:\n",
      "                  A       B       C       lab\n",
      "1980-01-01  4.0405  1.7246  804.74  0.006549\n",
      "1980-02-01  4.0963  1.7482  810.01  0.061876\n",
      "1980-03-01  4.3149  1.8519  860.13 -0.081406\n",
      "1980-04-01  3.9860  1.8220  790.11       NaN\n",
      "4.generate lab: \n",
      "                  A       B       C  lab\n",
      "1980-01-01  4.0405  1.7246  804.74    1\n",
      "1980-02-01  4.0963  1.7482  810.01    1\n",
      "1980-03-01  4.3149  1.8519  860.13    0\n"
     ]
    }
   ],
   "source": [
    "# 标签制作样例\n",
    "df = pd.DataFrame({\n",
    "   'A': [4.0405, 4.0963, 4.3149, 3.986],\n",
    "    'B': [1.7246, 1.7482, 1.8519, 1.822],\n",
    "     'C': [804.74, 810.01, 860.13, 790.11]},\n",
    "     index=['1980-01-01', '1980-02-01', '1980-03-01', '1980-04-01'])\n",
    "print('1.ori: \\n', df)\n",
    "df['lab'] = df['C'].pct_change()\n",
    "print('2.add pct_chg:\\n', df)\n",
    "# print(df.pct_change(axis='columns'))  # 可以指定按照行还是列进行计算的\n",
    "\n",
    "# 往上移动一行，即标签是今天预测明天\n",
    "df['lab'] = df['lab'].shift(periods=-1, axis=0) \n",
    "print('3.shift df:\\n', df)\n",
    "# 上移后，最后一行会出现nan值，丢弃\n",
    "df = df.dropna()\n",
    "\n",
    "import numpy as np\n",
    "df['lab'] = np.where(df['lab'] > 0, 1, 0)\n",
    "print('4.generate lab: \\n', df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "0it [00:00, ?it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "============================================================\n",
      "1.Train Data Prepare\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Processing 000333.XSHE: (600 / 600): : 600it [00:31, 19.26it/s]\n",
      "0it [00:00, ?it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data Process Complete!!!\n",
      "Data Shape: (125, 67)\n",
      "             open  close   high ...           AR  retained_earnings  lab\n",
      "2020-06-30  57.01  56.82  57.97 ...    99.243349       8.397603e+10    1\n",
      "2020-07-01  56.73  59.33  59.38 ...   121.392520       8.397603e+10    1\n",
      "2020-07-02  58.73  59.82  60.26 ...   147.406108       8.397603e+10    0\n",
      "2020-07-03  59.96  59.29  60.77 ...   139.727551       8.397603e+10    1\n",
      "2020-07-06  59.69  60.84  61.76 ...   147.176126       8.397603e+10    1\n",
      "\n",
      "[5 rows x 67 columns]\n",
      "Concat Data Shape: (1249, 67)\n",
      "x shape: (1249, 66)\n",
      "y shape: (1249,)\n",
      "============================================================\n",
      "2.Eval Data Prepare\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Processing 000333.XSHE: (600 / 600): : 600it [00:15, 38.97it/s]\n",
      "0it [00:00, ?it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data Process Complete!!!\n",
      "Data Shape: (29, 67)\n",
      "             open  close    high ...           AR  retained_earnings  lab\n",
      "2021-01-04  93.98  94.08   96.88 ...   121.187584       9.005129e+10    1\n",
      "2021-01-05  93.19  96.49   96.87 ...   128.701675       9.005129e+10    0\n",
      "2021-01-06  97.88  95.94   99.59 ...   121.527139       9.005129e+10    1\n",
      "2021-01-07  96.93  99.60  100.41 ...   124.348942       9.005129e+10    0\n",
      "2021-01-08  98.83  97.88   99.49 ...   113.924583       9.005129e+10    0\n",
      "\n",
      "[5 rows x 67 columns]\n",
      "Concat Data Shape: (290, 67)\n",
      "x shape: (290, 66)\n",
      "y shape: (290,)\n",
      "============================================================\n",
      "3.Test Data Prepare\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Processing 000333.XSHE: (600 / 600): : 600it [00:16, 36.39it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data Process Complete!!!\n",
      "Data Shape: (38, 67)\n",
      "             open  close   high ...          AR  retained_earnings  lab\n",
      "2021-03-31  78.68  78.14  78.85 ...   71.853763       9.005129e+10    1\n",
      "2021-04-01  77.92  81.18  81.61 ...   80.177029       9.005129e+10    1\n",
      "2021-04-02  81.25  82.78  84.10 ...   90.266181       9.005129e+10    0\n",
      "2021-04-06  82.82  80.18  83.34 ...   80.613002       9.005129e+10    0\n",
      "2021-04-07  80.18  78.60  80.29 ...   74.490695       9.005129e+10    0\n",
      "\n",
      "[5 rows x 67 columns]\n",
      "Concat Data Shape: (369, 67)\n",
      "x shape: (369, 66)\n",
      "y shape: (369,)\n"
     ]
    }
   ],
   "source": [
    "from jqfactor import get_factor_values\n",
    "from jqfactor import get_all_factors \n",
    "from tqdm import tqdm\n",
    "import numpy as np\n",
    "from jqlib.technical_analysis import *\n",
    "from jqdata import *\n",
    "\n",
    "# 获取沪深300股票列表\n",
    "hs300_stock_lst = get_index_stocks(market_pool)\n",
    "hs300_stock_lst = hs300_stock_lst[:stk_num]\n",
    "\n",
    "# 获取因子列表\n",
    "df_factors_info = get_all_factors()\n",
    "factor_lst = list(df_factors_info['factor'])[:factor_num]  # 只选择60个，选择太多，时间过长，而且有调用限制\n",
    "\n",
    "def prepare_data(hs300_stock_lst, factor_lst, start_time, end_time):\n",
    "    # 获取数据\n",
    "    df_dict = {}  # stk_code: df values\n",
    "\n",
    "    total_num = len(hs300_stock_lst) * len(factor_lst)  # 特征总数\n",
    "    pbar = tqdm(total_num)\n",
    "    cnt = 0\n",
    "    sample_code = ''  # 用于最后打印显示其中一支股票的数据信息\n",
    "\n",
    "    for code in hs300_stock_lst:\n",
    "        factor_dict = get_factor_values(securities=[code], factors=factor_lst, \n",
    "                                    start_date=start_time, end_date=end_time) \n",
    "        df_base = get_price(code, start_date=start_time, end_date=end_time, \n",
    "                   frequency='daily', skip_paused=True)  # , fill_paused=True, panel=False)\n",
    "\n",
    "        # 将因子数据和基础数据合并\n",
    "        for factor, df_ft_vals in factor_dict.items():\n",
    "            pbar.update(1)\n",
    "            cnt += 1\n",
    "            pbar.set_description(\"Processing %s: (%d / %d)\" % (code, cnt, total_num))\n",
    "            \n",
    "            # df_base过滤停牌后和df_base时间维度长度可能不一致\n",
    "            if len(df_base) == len(df_ft_vals):\n",
    "                df_base[factor] = df_ft_vals\n",
    "\n",
    "        if len(df_base):\n",
    "            sample_code = code\n",
    "            # 把数据表中的空值用0来代替\n",
    "            df_base.fillna(0, inplace=True)\n",
    "\n",
    "            # 添加标签\n",
    "            df_base['lab'] = df_base['close'].pct_change()\n",
    "\n",
    "            # 往上移动一行，即标签是今天预测明天\n",
    "            df_base['lab'] = df_base['lab'].shift(periods=-1, axis=0) \n",
    "\n",
    "            # 上移后，最后一行会出现nan值，丢弃\n",
    "            df_base = df_base.dropna()\n",
    "            # 生成1，0标签，1-涨，0-跌\n",
    "            df_base['lab'] = np.where(df_base['lab'] > 0, 1, 0)\n",
    "            df_dict[code] = df_base\n",
    "\n",
    "    pbar.close()\n",
    "\n",
    "    print('Data Process Complete!!!')\n",
    "    print('Data Shape:', df_dict[sample_code].shape)\n",
    "    print(df_dict[sample_code].head())\n",
    "\n",
    "    # 合并所有股票数据\n",
    "    df_all = pd.concat(df_dict.values(), sort=False)\n",
    "    print('Concat Data Shape:', df_all.shape)\n",
    "\n",
    "    y = df_all['lab']\n",
    "    # del df_all['lab']，这种方法会影响df_dict里的数据，后续df_dict里的lab列无法获取\n",
    "    x = df_all.loc[:, df_all.columns != 'lab']\n",
    "    print('x shape:', x.shape)\n",
    "    print('y shape:', y.shape)\n",
    "    return x, y, df_dict\n",
    "\n",
    "# 准备训练数据\n",
    "print('===' * 20)\n",
    "print('1.Train Data Prepare')\n",
    "x_train, y_train, df_train_dict = prepare_data(hs300_stock_lst, factor_lst, train[0], train[1])\n",
    "ft_names = x_train.columns\n",
    "\n",
    "# 准备验证数据\n",
    "print('===' * 20)\n",
    "print('2.Eval Data Prepare')\n",
    "x_eval, y_eval, df_eval_dict = prepare_data(hs300_stock_lst, factor_lst, eval[0], eval[1])\n",
    "\n",
    "# 准备测试数据\n",
    "print('===' * 20)\n",
    "print('3.Test Data Prepare')\n",
    "x_test, y_test, df_test_dict = prepare_data(hs300_stock_lst, factor_lst, test[0], test[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x\n",
      " open                                        0\n",
      "close                                       0\n",
      "high                                        0\n",
      "low                                         0\n",
      "volume                                      0\n",
      "money                                       0\n",
      "operating_profit_ttm                      124\n",
      "np_parent_company_owners_ttm              124\n",
      "net_interest_expense                      124\n",
      "sales_to_price_ratio                      124\n",
      "net_debt                                  124\n",
      "EBITDA                                    124\n",
      "total_operating_revenue_ttm               124\n",
      "OperateNetIncome                          124\n",
      "BR                                        124\n",
      "TVSTD6                                    124\n",
      "DAVOL20                                   124\n",
      "VDEA                                      124\n",
      "TVMA6                                     124\n",
      "DAVOL10                                   124\n",
      "interest_free_current_liability           124\n",
      "financial_liability                       124\n",
      "ATR14                                     124\n",
      "ATR6                                      124\n",
      "VDIFF                                     124\n",
      "administration_expense_ttm                124\n",
      "operating_revenue_ttm                     124\n",
      "gross_profit_ttm                          124\n",
      "total_operating_cost_ttm                  124\n",
      "value_change_profit_ttm                   124\n",
      "                                         ... \n",
      "DAVOL5                                    124\n",
      "cash_flow_to_price_ratio                  124\n",
      "VEMA26                                    124\n",
      "PSY                                       124\n",
      "net_invest_cash_flow_ttm                  124\n",
      "total_profit_ttm                          124\n",
      "operating_assets                          124\n",
      "money_flow_20                             124\n",
      "VEMA12                                    124\n",
      "financial_expense_ttm                     124\n",
      "financial_assets                          124\n",
      "MAWVAD                                    124\n",
      "net_operate_cash_flow_ttm                 124\n",
      "TVMA20                                    124\n",
      "goods_sale_and_service_render_cash_ttm    124\n",
      "TVSTD20                                   124\n",
      "net_profit_ttm                            124\n",
      "turnover_volatility                       124\n",
      "non_recurring_gain_loss                   124\n",
      "circulating_market_cap                    124\n",
      "VEMA10                                    124\n",
      "operating_liability                       124\n",
      "sale_expense_ttm                          124\n",
      "VEMA5                                     124\n",
      "EBIT                                      124\n",
      "asset_impairment_loss_ttm                 124\n",
      "net_working_capital                       124\n",
      "interest_carry_current_liability          124\n",
      "AR                                        124\n",
      "retained_earnings                         124\n",
      "Length: 66, dtype: int64\n",
      "y\n",
      " 0\n",
      "2020-06-30    1\n",
      "2020-07-01    1\n",
      "2020-07-02    1\n",
      "2020-07-03    1\n",
      "2020-07-06    0\n",
      "Name: lab, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "# 检查每一列是否包含nan值\n",
    "print('x\\n', x_train.isna().sum())\n",
    "print('y\\n', y_train.isna().sum())\n",
    "print(y_train.head())\n",
    "\n",
    "# 填充nan值\n",
    "x_train = x_train.fillna(0)\n",
    "y_train = y_train.fillna(0)\n",
    "\n",
    "x_eval = x_eval.fillna(0)\n",
    "y_eval = y_eval.fillna(0)\n",
    "\n",
    "x_test = x_eval.fillna(0)\n",
    "y_test = y_eval.fillna(0)\n",
    "\n",
    "# 对数据特征进行标准化处理\n",
    "# 此处，通过自己写公式的方式统计训练集的均值方差，然后保存，应用在eval和test集更好\n",
    "#  不太确定sklearn是否可以使用train中固定参数应用在eval/test上 \n",
    "from sklearn import preprocessing\n",
    "scaler=preprocessing.StandardScaler()\n",
    "x_train=scaler.fit_transform(x_train)\n",
    "x_eval=scaler.transform(x_eval)\n",
    "x_test=scaler.transform(x_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 5. 模型训练\n",
    "## 5.1 使用单支股票训练预测"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# ======= 1. 数据准备  ========\n",
    "code = list(df_train_dict.keys())[0]  # 取一支股票\n",
    "df_train_data = df_train_dict[code]\n",
    "#df_train_data.head()\n",
    "y_train1 = df_train_data['lab']\n",
    "x_train1 = df_train_data.loc[:, df_train_data.columns != 'lab']\n",
    "\n",
    "df_eval_data = df_eval_dict[code]\n",
    "y_test1 = df_eval_data['lab']\n",
    "x_test1 = df_eval_data.loc[:, df_eval_data.columns != 'lab']\n",
    "\n",
    "# 填充nan值\n",
    "x_train1 = x_train1.fillna(0)\n",
    "y_train1 = y_train1.fillna(0)\n",
    "\n",
    "x_test1 = x_test1.fillna(0)\n",
    "y_test1 = y_test1.fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "version 2.2.2\n",
      "The accuracy of the LGB is: 1.0\n",
      "The accuracy of the LGB is: 0.5517241379310345\n",
      "The confusion matrix result:\n",
      " [[10 8]\n",
      " [5 6]]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.6/site-packages/sklearn/preprocessing/label.py:151: DeprecationWarning: The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use `array.size > 0` to check that an array is not empty.\n",
      "  if diff:\n",
      "/opt/conda/lib/python3.6/site-packages/sklearn/preprocessing/label.py:151: DeprecationWarning: The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use `array.size > 0` to check that an array is not empty.\n",
      "  if diff:\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ======= 2. 模型训练  ========\n",
    "# sklearn接口形式\n",
    "import lightgbm as lgb\n",
    "import seaborn as sns\n",
    "print('version', lgb.__version__)\n",
    "\n",
    "# ## 导入LightGBM模型\n",
    "from lightgbm.sklearn import LGBMClassifier\n",
    "# ## 定义 LightGBM 模型 \n",
    "clf = LGBMClassifier(verbose=1)\n",
    "# # 在训练集上训练LightGBM模型\n",
    "clf.fit(x_train1, y_train1)\n",
    "## 在训练集和测试集上分布利用训练好的模型进行预测\n",
    "train_predict = clf.predict(x_train1)\n",
    "test_predict = clf.predict(x_test1)\n",
    "\n",
    "from sklearn import metrics\n",
    "\n",
    "## 利用accuracy（准确度）【预测正确的样本数目占总预测样本数目的比例】评估模型效果\n",
    "print('The accuracy of the LGB is:',metrics.accuracy_score(y_train1,train_predict))\n",
    "print('The accuracy of the LGB is:',metrics.accuracy_score(y_test1,test_predict))\n",
    "\n",
    "## 查看混淆矩阵 (预测值和真实值的各类情况统计矩阵)\n",
    "confusion_matrix_result = metrics.confusion_matrix(test_predict,y_test1)\n",
    "print('The confusion matrix result:\\n',confusion_matrix_result)\n",
    "\n",
    "# 利用热力图对于结果进行可视化\n",
    "plt.figure(figsize=(8, 6))\n",
    "sns.heatmap(confusion_matrix_result, annot=True, cmap='Blues')\n",
    "plt.xlabel('Predicted labels')\n",
    "plt.ylabel('True labels')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 5.2 使用所有股票训练预测"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "version 2.2.2\n",
      "[1]\tvalid_0's l1: 0.500712\tvalid_0's binary_logloss: 0.69546\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.5003\tvalid_0's binary_logloss: 0.69538\n",
      "[3]\tvalid_0's l1: 0.498817\tvalid_0's binary_logloss: 0.6929\n",
      "[4]\tvalid_0's l1: 0.497451\tvalid_0's binary_logloss: 0.690659\n",
      "[5]\tvalid_0's l1: 0.496592\tvalid_0's binary_logloss: 0.690056\n",
      "[6]\tvalid_0's l1: 0.495648\tvalid_0's binary_logloss: 0.688976\n",
      "[7]\tvalid_0's l1: 0.495256\tvalid_0's binary_logloss: 0.689819\n",
      "[8]\tvalid_0's l1: 0.495557\tvalid_0's binary_logloss: 0.690882\n",
      "[9]\tvalid_0's l1: 0.494932\tvalid_0's binary_logloss: 0.690215\n",
      "[10]\tvalid_0's l1: 0.494326\tvalid_0's binary_logloss: 0.689677\n",
      "[11]\tvalid_0's l1: 0.493087\tvalid_0's binary_logloss: 0.687191\n",
      "[12]\tvalid_0's l1: 0.492137\tvalid_0's binary_logloss: 0.685722\n",
      "[13]\tvalid_0's l1: 0.491421\tvalid_0's binary_logloss: 0.685584\n",
      "[14]\tvalid_0's l1: 0.490473\tvalid_0's binary_logloss: 0.68424\n",
      "[15]\tvalid_0's l1: 0.489028\tvalid_0's binary_logloss: 0.681863\n",
      "[16]\tvalid_0's l1: 0.488973\tvalid_0's binary_logloss: 0.682844\n",
      "[17]\tvalid_0's l1: 0.487793\tvalid_0's binary_logloss: 0.681269\n",
      "[18]\tvalid_0's l1: 0.487945\tvalid_0's binary_logloss: 0.682077\n",
      "[19]\tvalid_0's l1: 0.486773\tvalid_0's binary_logloss: 0.679553\n",
      "[20]\tvalid_0's l1: 0.485598\tvalid_0's binary_logloss: 0.67898\n",
      "[21]\tvalid_0's l1: 0.484816\tvalid_0's binary_logloss: 0.678663\n",
      "[22]\tvalid_0's l1: 0.4848\tvalid_0's binary_logloss: 0.679351\n",
      "[23]\tvalid_0's l1: 0.483954\tvalid_0's binary_logloss: 0.67854\n",
      "[24]\tvalid_0's l1: 0.483461\tvalid_0's binary_logloss: 0.678255\n",
      "[25]\tvalid_0's l1: 0.483186\tvalid_0's binary_logloss: 0.679139\n",
      "[26]\tvalid_0's l1: 0.483119\tvalid_0's binary_logloss: 0.679614\n",
      "[27]\tvalid_0's l1: 0.481977\tvalid_0's binary_logloss: 0.678449\n",
      "[28]\tvalid_0's l1: 0.481831\tvalid_0's binary_logloss: 0.678835\n",
      "[29]\tvalid_0's l1: 0.481925\tvalid_0's binary_logloss: 0.680099\n",
      "Early stopping, best iteration is:\n",
      "[24]\tvalid_0's l1: 0.483461\tvalid_0's binary_logloss: 0.678255\n",
      "The train accuracy of the LGB is: 0.8686949559647719\n",
      "The eval accuracy of the LGB is: 0.5551724137931034\n",
      "The test accuracy of the LGB is: 0.5551724137931034\n",
      "The confusion matrix result:\n",
      " [[77 72]\n",
      " [57 84]]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.6/site-packages/sklearn/preprocessing/label.py:151: DeprecationWarning: The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use `array.size > 0` to check that an array is not empty.\n",
      "  if diff:\n",
      "/opt/conda/lib/python3.6/site-packages/sklearn/preprocessing/label.py:151: DeprecationWarning: The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use `array.size > 0` to check that an array is not empty.\n",
      "  if diff:\n",
      "/opt/conda/lib/python3.6/site-packages/sklearn/preprocessing/label.py:151: DeprecationWarning: The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use `array.size > 0` to check that an array is not empty.\n",
      "  if diff:\n"
     ]
    },
    {
     "data": {
      "image/png": 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h/sg0NCVJlWhAo+lCIEmSStlpSpKq0IRbTgxNSVIVmjD1aWhKkqpgpylJUqH6I7MZ3bAkSVWw05QkVcHpWUmSCjVh6tPQlCRVoQmdZhOCXZKkKthpSpKqUH+faWhKkirRgNlZQ1OSVIe+BvSahqYkqQp2mpIkVSIi9gT+GZgInA/MAI4FngSWZubRQ41haEqSqhAdnJ6NiAnAZcAxmbmkve+LwMmZeW3pOIamJKkKHZ6ePQi4c21gtm0FPDGcQQxNSVIVOrwQaA9gVURcCWwOnAYkcG60nqrwjcz80lCDGJqSpCqMtNOMiLnA3H675mXmvPbPmwHTgCOBHYDLMnPv9nGbAddHxB2Zedtg5zA0JUljQjsg523g7SeA72fmauCBiJjS77hnI2IhsDswaGj6GD1JUhUiRvYawg3AnIjoi4iZwJMRsW3rvDEO2A+4a6hB7DQlSVXo5OrZzLw/IuYDt7d3nQKcFxHb03qC3xWZuWiocQxNSVIV+jr8cIPMPAc4p9+uQadiB+L0rCRJhew0JUlV6OT07MZiaEqSquCzZyVJKmSnKUlSoU4vBNoYDM0elJkcuN8bmbXLrgC890/+lG9f9s117z/++FKOfs/7+PDcj3SrRKnIuZ8+ht13nk4mnPzfvsndD/wWgI998B28ff/Xcth/+qcuV6ixxtDsQcuXL2fWrF246JKvr9t3xJFHrfv5L085mbe89eAuVCaVe/MbdmK7aVN42we+wL577shfz/1jjvvE19hx5tbst+eO3S5PL0MTpme95aQHPfO73zFlyy0HfO/pp5/i0Ucf4TW77TbKVUnD88yzK5k2dTLjxvUxfevJPPPsSgD+/tR38/kLir/pSRXp8BOBNgo7zR60Zs3z3HfvvXzg+OPYYsoUPvaJ05g5c3sArp4/nzmHv7PLFUpD+9n9v+Xa2+/h1ks+zvPPv8B7Tzmf447Yl1vuuJ+Hly7rdnl6GervMzsYmhFxxmDvZ+ZZnTq3BvfqHXfiu9fdCMB13/8enznzDM7/6gUAXH3VlZx3/le7WZ5UZOqUzXjHAbtzzqU38v45s3n7Abvz/jlv5F0nncfMaQPPpKhufQ2456ST07OHANOB/7OB1wZFxNyIWBwRi//1Kxt6YL02hgPfehAPPvgAAD+96y6mT5/O1KlTu1yVNLT3z5nNdT/4Of/z6h/xvlPP51Nz57DXa3fgwe99llsv/Tj7vX5H/ve/nNTtMjXGdHJ69t3AfOD0zHxyOAf2/3qXlWvIDtTW05Yte5rNN5/MuHHj+Lc7FrPrrq8B4DuXf5sj3vXuLlcnlXl25SomTZwAwKSJE3hu1fPsfsSZAOwwYyu+ctaf8c6PnNvFCjVc9feZHQzNzFwWEYdk5gudOodenvvuvZfP/8PZbLrppkyYMIFPnXEmK1eu5Ic/uI2/+utPd7s8qcg3rlnMYZ/dgxsuOJW+vj7+4uxvdbskjVQDUjMy627k7DQ1Fmw522lCjQ3PLTm3Y9G26MHfjejP+3133qLjsestJ5IkFfKWE0lSFRqweNbQlCTVoQGZaWhKkirRgNQ0NCVJVfDZs5IkjSF2mpKkKrgQSJKkQg3ITENTklSJBqSmoSlJqoILgSRJGkPsNCVJVXAhkCRJhRqQmYamJKkSDUhNr2lKklTITlOSVIUmrJ41NCVJVXAhkCRJhRqQmYamJKkSDUhNFwJJklTITlOSVAUXAkmSVMiFQJIkFWpAZnpNU5KkUnaakqQ6NKDVNDQlSVVwIZAkSYVcCCRJUqEGZKYLgSRJKmWnKUmqQwNaTUNTklQFFwJJklTIhUCSJBVqQGa6EEiSpFJ2mpKkOjSg1TQ0JUlVcCGQJEmFmrAQyGuakiQVMjQlSVWIEb6GHD9iz4i4JSJ+HBEfjogZEXFDRCyKiNNLanR6VpJUhw5Oz0bEBOAy4JjMXNLe9xXgHOAKYGFEXJ6Zdw82jp2mJKkKMcJ/hnAQcOfawGw7FLgmMxO4pr09KDtNSVIVOrwQaA9gVURcCWwOnAZMysxV7fcfB3YaahBDU5I0JkTEXGBuv13zMnNe++fNgGnAkcAOtKZqJ/Q/fL3tARmakqQqjLTRbAfkvA28/QTw/cxcDTwQEVOAFRExMTNXAlsDjw51Dq9pSpKqEDGy1xBuAOZERF9EzASeBG5p7wvgcGDhUIPYaUqSKtG5i5qZeX9EzAdub+86BXgIuITW9c0Fmbl4qHEMTUlSFTr9RKDMPIfWLSb9HTKcMZyelSSpkJ2mJKkKDXj0rKEpSapDEx7YbmhKkqrQhK8G85qmJEmF7DQlSXWov9E0NCVJdWhAZhqakqQ6uBBIkqRCLgSSJGkMsdOUJNWh/kbT0JQk1aEBmWloSpLq4EIgSZIKuRBIkqQxxE5TklSFJkzP2mlKklTITlOSVAU7TUmSxhA7TUlSFZqwetbQlCRVoQnTs4amJKkKDchMQ1OSVIkGpKYLgSRJKmSnKUmqgguBJEkq5EIgSZIKNSAzDU1JUiUakJouBJIkqZCdpiSpCi4EkiSpUBMWAkVmdrsGdVlEzM3Med2uQxopf5fVaV7TFMDcbhcgbST+LqujDE1JkgoZmpIkFTI0BeA1II0V/i6ro1wIJElSITtNSZIKGZo9LiJOjYhFEXFLROzY7XqklysipkTETRFxZrdr0dhlaPawiJgJHAscAPwt8N+7W5H08kTEJsBVwL3drkVjm6HZ2w4Frs3MNcD1wJu7XI/0srR/h48GftjtWjS2GZq9bRrwBEC2VoT9PiImdLck6eXJzMe7XYPGPkOzt43npV/GE+19kqQBGJq97TFgKkBEBDA+M5/tbkmSVC9Ds7fdDLwjIsbRur754y7XI0lV86vBelhm/iIivg78AFgNnNDlkiSpaj4RSJKkQk7PSpJUyNCUJKmQoSlJUiFDU5KkQoamJEmFDE1JkgoZmhrTImJNRNwaEXdGxJ+PYJybIuLVEbFtRPzdIJ87fJjjPjTAvgsj4qhBjrkwIg4uHP/EiPjicGqStGGGpsa6FZl5IPAW4BMR8aqRDJaZSzPz0wO9134U4ZkjGV9S3QxN9YTMXA78HHhVu/v6h4i4PiI+GhGbRsQlEbEwIr4dERMBIuJTEXFHRHyLF5/R++qIuLP987YRcXVE3BYRXwM+CuzZ7mznRMQ2EXFFe/v8dqgSEee1v/j7AuAVg9UdEfMi4uaIWBIRs/u9dWy7/oURMaP92dntjvhHEfHhAcY6v/3eHRGxw4j/p0o9yMfoqSe0O8ydgPuA1wFHAHtl5nMR8THgusy8sD31ekJEXAv8KbA3sCXw0ADD/i3wvzLzgoiIzMyI+Hi7syUizgW+mJk3RcQltJ7zuwrYOTP3jYjXAScOUfpHM3NNRLyHVih/oL1/eWYeGhH/BfgkcArwReBw4Fng7oi4rN9//zbAwZn5moiYmJkrh/P/T1KLoamx7pURsRB4DvhwZi5vN3w3ZeZz7c8cCMyMiBOBVwLfAd4A/LD95caPR8Q9A4y9P/B3sO77SNd3IPCGiFgDTAGm0+pYF7aP+VlEPLGhwtud6Wci4iBgEi8N7rVftrwQOCYipgCvB65s709gRr/PPwE81O6a/wp4YEPnlbRhhqbGuhWZedAA+9fvtP4iM29eu9Hu7PoH4ZoBxogB9q3v2Mz8v/3G/cuCcdd6G61gPqj9OmmIcy3NzINfUmDE/tAK9YiYQ6uzvTEi/igz7yuoX1I/XtOUWl3buwAiYlxEbAHcBewfEZtExFbAHgMctxh4x9rj2vv+PSJeOcC4r4iIzYA7gbe29+0KTBukri2AhzLzeVpda39vbv/7IGBJZi4DVkbEnu2xp/b/cERsCmySmV8D5tOaopY0TIamBOcAMyLidmARsEdm3g9cTus7Rv+VVtit7wxaU6O3Axe1910M3BIR72y/f1j7/VuA6Zl5PfDriPgR8De0FidtyLXAbu3rq6vWe++UiPgJcAxwdnvficC/RMQPgG+s9/ntgEURcSuwM/D9Qc4raQP8ajBJkgrZaUqSVMjQlCSpkKEpSVIhQ1OSpEKGpiRJhQxNSZIKGZqSJBUyNCVJKmRoSpJU6P8BpRUazHkUEzwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 576x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# sklearn接口形式\n",
    "import lightgbm as lgb\n",
    "import seaborn as sns\n",
    "print('version', lgb.__version__)\n",
    "\n",
    "# ## 导入LightGBM模型\n",
    "from lightgbm.sklearn import LGBMClassifier\n",
    "# ## 定义 LightGBM 模型，verbose为1显示训练过程 \n",
    "clf = LGBMClassifier(objective='binary', num_leaves=50, learning_rate=0.05, n_estimators=100, verbose=1)\n",
    "# # 在训练集上训练LightGBM模型\n",
    "clf.fit(x_train, y_train, eval_set=[(x_eval, y_eval)], eval_metric='l1', early_stopping_rounds=5)\n",
    "## 在训练集和测试集上分布利用训练好的模型进行预测\n",
    "train_predict = clf.predict(x_train)\n",
    "eval_predict = clf.predict(x_eval)\n",
    "test_predict = clf.predict(x_test)\n",
    "\n",
    "from sklearn import metrics\n",
    "\n",
    "## 利用accuracy（准确度）【预测正确的样本数目占总预测样本数目的比例】评估模型效果\n",
    "print('The train accuracy of the LGB is:',metrics.accuracy_score(y_train,train_predict))\n",
    "print('The eval accuracy of the LGB is:',metrics.accuracy_score(y_eval,eval_predict))\n",
    "print('The test accuracy of the LGB is:',metrics.accuracy_score(y_test,test_predict))\n",
    "\n",
    "## 查看混淆矩阵 (预测值和真实值的各类情况统计矩阵)\n",
    "confusion_matrix_result = metrics.confusion_matrix(test_predict,y_test)\n",
    "print('The confusion matrix result:\\n',confusion_matrix_result)\n",
    "\n",
    "# 利用热力图对于结果进行可视化\n",
    "plt.figure(figsize=(8, 6))\n",
    "sns.heatmap(confusion_matrix_result, annot=True, cmap='Blues')\n",
    "plt.xlabel('Predicted labels')\n",
    "plt.ylabel('True labels')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5.3 模型参数调优"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "version 2.2.2\n",
      "Fitting 5 folds for each of 54 candidates, totalling 270 fits\n",
      "[1]\tvalid_0's l1: 0.501149\tvalid_0's binary_logloss: 0.696022\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501007\tvalid_0's binary_logloss: 0.695745\n",
      "[3]\tvalid_0's l1: 0.500871\tvalid_0's binary_logloss: 0.695495\n",
      "[4]\tvalid_0's l1: 0.500774\tvalid_0's binary_logloss: 0.695296\n",
      "[5]\tvalid_0's l1: 0.500636\tvalid_0's binary_logloss: 0.695055\n",
      "[6]\tvalid_0's l1: 0.500541\tvalid_0's binary_logloss: 0.694882\n",
      "[7]\tvalid_0's l1: 0.500405\tvalid_0's binary_logloss: 0.694661\n",
      "[8]\tvalid_0's l1: 0.500311\tvalid_0's binary_logloss: 0.694513\n",
      "[9]\tvalid_0's l1: 0.500212\tvalid_0's binary_logloss: 0.69437\n",
      "[10]\tvalid_0's l1: 0.500079\tvalid_0's binary_logloss: 0.694176\n",
      "[11]\tvalid_0's l1: 0.499982\tvalid_0's binary_logloss: 0.694057\n",
      "[12]\tvalid_0's l1: 0.499884\tvalid_0's binary_logloss: 0.693953\n",
      "[13]\tvalid_0's l1: 0.49977\tvalid_0's binary_logloss: 0.693817\n",
      "[14]\tvalid_0's l1: 0.499681\tvalid_0's binary_logloss: 0.693747\n",
      "[15]\tvalid_0's l1: 0.499581\tvalid_0's binary_logloss: 0.69353\n",
      "[16]\tvalid_0's l1: 0.499468\tvalid_0's binary_logloss: 0.693425\n",
      "[17]\tvalid_0's l1: 0.499352\tvalid_0's binary_logloss: 0.693303\n",
      "[18]\tvalid_0's l1: 0.499246\tvalid_0's binary_logloss: 0.693232\n",
      "[19]\tvalid_0's l1: 0.49915\tvalid_0's binary_logloss: 0.69316\n",
      "[20]\tvalid_0's l1: 0.499135\tvalid_0's binary_logloss: 0.693231\n",
      "[21]\tvalid_0's l1: 0.499127\tvalid_0's binary_logloss: 0.693327\n",
      "[22]\tvalid_0's l1: 0.499006\tvalid_0's binary_logloss: 0.69309\n",
      "[23]\tvalid_0's l1: 0.498867\tvalid_0's binary_logloss: 0.692944\n",
      "[24]\tvalid_0's l1: 0.498829\tvalid_0's binary_logloss: 0.692995\n",
      "[25]\tvalid_0's l1: 0.498815\tvalid_0's binary_logloss: 0.693107\n",
      "[26]\tvalid_0's l1: 0.498696\tvalid_0's binary_logloss: 0.692889\n",
      "[27]\tvalid_0's l1: 0.49866\tvalid_0's binary_logloss: 0.692968\n",
      "[28]\tvalid_0's l1: 0.498565\tvalid_0's binary_logloss: 0.692925\n",
      "[29]\tvalid_0's l1: 0.498528\tvalid_0's binary_logloss: 0.693018\n",
      "[30]\tvalid_0's l1: 0.498515\tvalid_0's binary_logloss: 0.693168\n",
      "[31]\tvalid_0's l1: 0.498498\tvalid_0's binary_logloss: 0.693225\n",
      "Early stopping, best iteration is:\n",
      "[26]\tvalid_0's l1: 0.498696\tvalid_0's binary_logloss: 0.692889\n",
      "[1]\tvalid_0's l1: 0.50121\tvalid_0's binary_logloss: 0.696223\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501076\tvalid_0's binary_logloss: 0.695997\n",
      "[3]\tvalid_0's l1: 0.500942\tvalid_0's binary_logloss: 0.695784\n",
      "[4]\tvalid_0's l1: 0.500828\tvalid_0's binary_logloss: 0.695627\n",
      "[5]\tvalid_0's l1: 0.500744\tvalid_0's binary_logloss: 0.695523\n",
      "[6]\tvalid_0's l1: 0.500631\tvalid_0's binary_logloss: 0.69539\n",
      "[7]\tvalid_0's l1: 0.500565\tvalid_0's binary_logloss: 0.695353\n",
      "[8]\tvalid_0's l1: 0.500437\tvalid_0's binary_logloss: 0.695196\n",
      "[9]\tvalid_0's l1: 0.500356\tvalid_0's binary_logloss: 0.69513\n",
      "[10]\tvalid_0's l1: 0.500295\tvalid_0's binary_logloss: 0.695131\n",
      "[11]\tvalid_0's l1: 0.500202\tvalid_0's binary_logloss: 0.694949\n",
      "[12]\tvalid_0's l1: 0.50008\tvalid_0's binary_logloss: 0.694711\n",
      "[13]\tvalid_0's l1: 0.500004\tvalid_0's binary_logloss: 0.694679\n",
      "[14]\tvalid_0's l1: 0.499914\tvalid_0's binary_logloss: 0.694537\n",
      "[15]\tvalid_0's l1: 0.499728\tvalid_0's binary_logloss: 0.694166\n",
      "[16]\tvalid_0's l1: 0.499653\tvalid_0's binary_logloss: 0.694151\n",
      "[17]\tvalid_0's l1: 0.499498\tvalid_0's binary_logloss: 0.693874\n",
      "[18]\tvalid_0's l1: 0.499424\tvalid_0's binary_logloss: 0.693874\n",
      "[19]\tvalid_0's l1: 0.499337\tvalid_0's binary_logloss: 0.693781\n",
      "[20]\tvalid_0's l1: 0.499189\tvalid_0's binary_logloss: 0.693566\n",
      "[21]\tvalid_0's l1: 0.499009\tvalid_0's binary_logloss: 0.693259\n",
      "[22]\tvalid_0's l1: 0.498872\tvalid_0's binary_logloss: 0.693085\n",
      "[23]\tvalid_0's l1: 0.498723\tvalid_0's binary_logloss: 0.692869\n",
      "[24]\tvalid_0's l1: 0.498667\tvalid_0's binary_logloss: 0.692942\n",
      "[25]\tvalid_0's l1: 0.498491\tvalid_0's binary_logloss: 0.692679\n",
      "[26]\tvalid_0's l1: 0.498348\tvalid_0's binary_logloss: 0.692499\n",
      "[27]\tvalid_0's l1: 0.498224\tvalid_0's binary_logloss: 0.692366\n",
      "[28]\tvalid_0's l1: 0.49801\tvalid_0's binary_logloss: 0.692059\n",
      "[29]\tvalid_0's l1: 0.497867\tvalid_0's binary_logloss: 0.691898\n",
      "[30]\tvalid_0's l1: 0.49782\tvalid_0's binary_logloss: 0.69203\n",
      "[31]\tvalid_0's l1: 0.497712\tvalid_0's binary_logloss: 0.691957\n",
      "[32]\tvalid_0's l1: 0.497574\tvalid_0's binary_logloss: 0.691807\n",
      "[33]\tvalid_0's l1: 0.497455\tvalid_0's binary_logloss: 0.69172\n",
      "[34]\tvalid_0's l1: 0.497349\tvalid_0's binary_logloss: 0.691647\n",
      "[35]\tvalid_0's l1: 0.497212\tvalid_0's binary_logloss: 0.69151\n",
      "[36]\tvalid_0's l1: 0.497167\tvalid_0's binary_logloss: 0.691669\n",
      "[37]\tvalid_0's l1: 0.497031\tvalid_0's binary_logloss: 0.691564\n",
      "[38]\tvalid_0's l1: 0.496825\tvalid_0's binary_logloss: 0.691305\n",
      "[39]\tvalid_0's l1: 0.496711\tvalid_0's binary_logloss: 0.691258\n",
      "[40]\tvalid_0's l1: 0.49662\tvalid_0's binary_logloss: 0.691185\n",
      "[41]\tvalid_0's l1: 0.496464\tvalid_0's binary_logloss: 0.69103\n",
      "[42]\tvalid_0's l1: 0.49642\tvalid_0's binary_logloss: 0.691212\n",
      "[43]\tvalid_0's l1: 0.496283\tvalid_0's binary_logloss: 0.691126\n",
      "[44]\tvalid_0's l1: 0.496152\tvalid_0's binary_logloss: 0.691067\n",
      "[45]\tvalid_0's l1: 0.495992\tvalid_0's binary_logloss: 0.690933\n",
      "[46]\tvalid_0's l1: 0.495858\tvalid_0's binary_logloss: 0.690874\n",
      "[47]\tvalid_0's l1: 0.495866\tvalid_0's binary_logloss: 0.69107\n",
      "[48]\tvalid_0's l1: 0.49569\tvalid_0's binary_logloss: 0.690862\n",
      "[49]\tvalid_0's l1: 0.495563\tvalid_0's binary_logloss: 0.690777\n",
      "[50]\tvalid_0's l1: 0.495476\tvalid_0's binary_logloss: 0.690724\n",
      "[51]\tvalid_0's l1: 0.495469\tvalid_0's binary_logloss: 0.690933\n",
      "[52]\tvalid_0's l1: 0.49532\tvalid_0's binary_logloss: 0.69086\n",
      "[53]\tvalid_0's l1: 0.495172\tvalid_0's binary_logloss: 0.690745\n",
      "[54]\tvalid_0's l1: 0.495087\tvalid_0's binary_logloss: 0.690698\n",
      "[55]\tvalid_0's l1: 0.495002\tvalid_0's binary_logloss: 0.690656\n",
      "[56]\tvalid_0's l1: 0.494786\tvalid_0's binary_logloss: 0.690417\n",
      "[57]\tvalid_0's l1: 0.494702\tvalid_0's binary_logloss: 0.690381\n",
      "[58]\tvalid_0's l1: 0.494696\tvalid_0's binary_logloss: 0.690602\n",
      "[59]\tvalid_0's l1: 0.494567\tvalid_0's binary_logloss: 0.690553\n",
      "[60]\tvalid_0's l1: 0.494465\tvalid_0's binary_logloss: 0.690479\n",
      "[61]\tvalid_0's l1: 0.494383\tvalid_0's binary_logloss: 0.690451\n",
      "[62]\tvalid_0's l1: 0.494247\tvalid_0's binary_logloss: 0.690308\n",
      "[63]\tvalid_0's l1: 0.494165\tvalid_0's binary_logloss: 0.690285\n",
      "[64]\tvalid_0's l1: 0.494038\tvalid_0's binary_logloss: 0.690172\n",
      "[65]\tvalid_0's l1: 0.493985\tvalid_0's binary_logloss: 0.690192\n",
      "[66]\tvalid_0's l1: 0.493881\tvalid_0's binary_logloss: 0.690116\n",
      "[67]\tvalid_0's l1: 0.493902\tvalid_0's binary_logloss: 0.690384\n",
      "[68]\tvalid_0's l1: 0.493756\tvalid_0's binary_logloss: 0.690291\n",
      "[69]\tvalid_0's l1: 0.493607\tvalid_0's binary_logloss: 0.690123\n",
      "[70]\tvalid_0's l1: 0.493628\tvalid_0's binary_logloss: 0.690401\n",
      "[71]\tvalid_0's l1: 0.493481\tvalid_0's binary_logloss: 0.690244\n",
      "Early stopping, best iteration is:\n",
      "[66]\tvalid_0's l1: 0.493881\tvalid_0's binary_logloss: 0.690116\n",
      "[1]\tvalid_0's l1: 0.501228\tvalid_0's binary_logloss: 0.696199\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501127\tvalid_0's binary_logloss: 0.695984\n",
      "[3]\tvalid_0's l1: 0.500967\tvalid_0's binary_logloss: 0.695633\n",
      "[4]\tvalid_0's l1: 0.500868\tvalid_0's binary_logloss: 0.695427\n",
      "[5]\tvalid_0's l1: 0.50071\tvalid_0's binary_logloss: 0.695087\n",
      "[6]\tvalid_0's l1: 0.500613\tvalid_0's binary_logloss: 0.69489\n",
      "[7]\tvalid_0's l1: 0.50038\tvalid_0's binary_logloss: 0.694409\n",
      "[8]\tvalid_0's l1: 0.500284\tvalid_0's binary_logloss: 0.69422\n",
      "[9]\tvalid_0's l1: 0.500054\tvalid_0's binary_logloss: 0.693754\n",
      "[10]\tvalid_0's l1: 0.49996\tvalid_0's binary_logloss: 0.693573\n",
      "[11]\tvalid_0's l1: 0.499807\tvalid_0's binary_logloss: 0.693253\n",
      "[12]\tvalid_0's l1: 0.49958\tvalid_0's binary_logloss: 0.692806\n",
      "[13]\tvalid_0's l1: 0.499488\tvalid_0's binary_logloss: 0.692615\n",
      "[14]\tvalid_0's l1: 0.499337\tvalid_0's binary_logloss: 0.692307\n",
      "[15]\tvalid_0's l1: 0.499246\tvalid_0's binary_logloss: 0.692143\n",
      "[16]\tvalid_0's l1: 0.499025\tvalid_0's binary_logloss: 0.691717\n",
      "[17]\tvalid_0's l1: 0.498936\tvalid_0's binary_logloss: 0.69156\n",
      "[18]\tvalid_0's l1: 0.498717\tvalid_0's binary_logloss: 0.691148\n",
      "[19]\tvalid_0's l1: 0.498633\tvalid_0's binary_logloss: 0.690986\n",
      "[20]\tvalid_0's l1: 0.498511\tvalid_0's binary_logloss: 0.69074\n",
      "[21]\tvalid_0's l1: 0.498425\tvalid_0's binary_logloss: 0.690594\n",
      "[22]\tvalid_0's l1: 0.498384\tvalid_0's binary_logloss: 0.690514\n",
      "[23]\tvalid_0's l1: 0.498311\tvalid_0's binary_logloss: 0.690368\n",
      "[24]\tvalid_0's l1: 0.498235\tvalid_0's binary_logloss: 0.690197\n",
      "[25]\tvalid_0's l1: 0.498183\tvalid_0's binary_logloss: 0.690102\n",
      "[26]\tvalid_0's l1: 0.498123\tvalid_0's binary_logloss: 0.689981\n",
      "[27]\tvalid_0's l1: 0.498048\tvalid_0's binary_logloss: 0.689817\n",
      "[28]\tvalid_0's l1: 0.497917\tvalid_0's binary_logloss: 0.689591\n",
      "[29]\tvalid_0's l1: 0.497846\tvalid_0's binary_logloss: 0.689455\n",
      "[30]\tvalid_0's l1: 0.497716\tvalid_0's binary_logloss: 0.689239\n",
      "[31]\tvalid_0's l1: 0.497642\tvalid_0's binary_logloss: 0.68908\n",
      "[32]\tvalid_0's l1: 0.497548\tvalid_0's binary_logloss: 0.688929\n",
      "[33]\tvalid_0's l1: 0.49742\tvalid_0's binary_logloss: 0.688723\n",
      "[34]\tvalid_0's l1: 0.497327\tvalid_0's binary_logloss: 0.688577\n",
      "[35]\tvalid_0's l1: 0.4972\tvalid_0's binary_logloss: 0.688382\n",
      "[36]\tvalid_0's l1: 0.497136\tvalid_0's binary_logloss: 0.6883\n",
      "[37]\tvalid_0's l1: 0.49701\tvalid_0's binary_logloss: 0.688115\n",
      "[38]\tvalid_0's l1: 0.496934\tvalid_0's binary_logloss: 0.687958\n",
      "[39]\tvalid_0's l1: 0.496844\tvalid_0's binary_logloss: 0.687821\n",
      "[40]\tvalid_0's l1: 0.496736\tvalid_0's binary_logloss: 0.687617\n",
      "[41]\tvalid_0's l1: 0.496612\tvalid_0's binary_logloss: 0.687442\n",
      "[42]\tvalid_0's l1: 0.496549\tvalid_0's binary_logloss: 0.687369\n",
      "[43]\tvalid_0's l1: 0.496393\tvalid_0's binary_logloss: 0.687107\n",
      "[44]\tvalid_0's l1: 0.496304\tvalid_0's binary_logloss: 0.686979\n",
      "[45]\tvalid_0's l1: 0.496275\tvalid_0's binary_logloss: 0.686964\n",
      "[46]\tvalid_0's l1: 0.496154\tvalid_0's binary_logloss: 0.686807\n",
      "[47]\tvalid_0's l1: 0.496091\tvalid_0's binary_logloss: 0.686651\n",
      "[48]\tvalid_0's l1: 0.49603\tvalid_0's binary_logloss: 0.686587\n",
      "[49]\tvalid_0's l1: 0.495877\tvalid_0's binary_logloss: 0.686339\n",
      "[50]\tvalid_0's l1: 0.495815\tvalid_0's binary_logloss: 0.686184\n",
      "[51]\tvalid_0's l1: 0.495728\tvalid_0's binary_logloss: 0.686067\n",
      "[52]\tvalid_0's l1: 0.495576\tvalid_0's binary_logloss: 0.685827\n",
      "[53]\tvalid_0's l1: 0.495562\tvalid_0's binary_logloss: 0.685827\n",
      "[54]\tvalid_0's l1: 0.495445\tvalid_0's binary_logloss: 0.68569\n",
      "[55]\tvalid_0's l1: 0.495309\tvalid_0's binary_logloss: 0.685424\n",
      "[56]\tvalid_0's l1: 0.495238\tvalid_0's binary_logloss: 0.685338\n",
      "[57]\tvalid_0's l1: 0.495224\tvalid_0's binary_logloss: 0.685343\n",
      "[58]\tvalid_0's l1: 0.495076\tvalid_0's binary_logloss: 0.685117\n",
      "[59]\tvalid_0's l1: 0.494943\tvalid_0's binary_logloss: 0.684859\n",
      "[60]\tvalid_0's l1: 0.494828\tvalid_0's binary_logloss: 0.684736\n",
      "[61]\tvalid_0's l1: 0.494696\tvalid_0's binary_logloss: 0.684485\n",
      "[62]\tvalid_0's l1: 0.494624\tvalid_0's binary_logloss: 0.684395\n",
      "[63]\tvalid_0's l1: 0.494611\tvalid_0's binary_logloss: 0.684402\n",
      "[64]\tvalid_0's l1: 0.494465\tvalid_0's binary_logloss: 0.684192\n",
      "[65]\tvalid_0's l1: 0.494335\tvalid_0's binary_logloss: 0.68395\n",
      "[66]\tvalid_0's l1: 0.494223\tvalid_0's binary_logloss: 0.683838\n",
      "[67]\tvalid_0's l1: 0.494154\tvalid_0's binary_logloss: 0.683762\n",
      "[68]\tvalid_0's l1: 0.494026\tvalid_0's binary_logloss: 0.683527\n",
      "[69]\tvalid_0's l1: 0.494013\tvalid_0's binary_logloss: 0.683536\n",
      "[70]\tvalid_0's l1: 0.493902\tvalid_0's binary_logloss: 0.683431\n",
      "[71]\tvalid_0's l1: 0.493898\tvalid_0's binary_logloss: 0.683426\n",
      "[72]\tvalid_0's l1: 0.493757\tvalid_0's binary_logloss: 0.683237\n",
      "[73]\tvalid_0's l1: 0.493688\tvalid_0's binary_logloss: 0.683157\n",
      "[74]\tvalid_0's l1: 0.493673\tvalid_0's binary_logloss: 0.68317\n",
      "[75]\tvalid_0's l1: 0.493547\tvalid_0's binary_logloss: 0.682944\n",
      "[76]\tvalid_0's l1: 0.493439\tvalid_0's binary_logloss: 0.682851\n",
      "[77]\tvalid_0's l1: 0.493372\tvalid_0's binary_logloss: 0.682783\n",
      "[78]\tvalid_0's l1: 0.493369\tvalid_0's binary_logloss: 0.682779\n",
      "[79]\tvalid_0's l1: 0.493337\tvalid_0's binary_logloss: 0.68276\n",
      "[80]\tvalid_0's l1: 0.493199\tvalid_0's binary_logloss: 0.682583\n",
      "[81]\tvalid_0's l1: 0.493075\tvalid_0's binary_logloss: 0.682365\n",
      "[82]\tvalid_0's l1: 0.493038\tvalid_0's binary_logloss: 0.682344\n",
      "[83]\tvalid_0's l1: 0.492932\tvalid_0's binary_logloss: 0.682264\n",
      "[84]\tvalid_0's l1: 0.492864\tvalid_0's binary_logloss: 0.682194\n",
      "[85]\tvalid_0's l1: 0.492861\tvalid_0's binary_logloss: 0.68219\n",
      "[86]\tvalid_0's l1: 0.492825\tvalid_0's binary_logloss: 0.682176\n",
      "[87]\tvalid_0's l1: 0.492759\tvalid_0's binary_logloss: 0.682115\n",
      "[88]\tvalid_0's l1: 0.492637\tvalid_0's binary_logloss: 0.681903\n",
      "[89]\tvalid_0's l1: 0.492593\tvalid_0's binary_logloss: 0.681932\n",
      "[90]\tvalid_0's l1: 0.492519\tvalid_0's binary_logloss: 0.681856\n",
      "[91]\tvalid_0's l1: 0.492516\tvalid_0's binary_logloss: 0.681853\n",
      "[92]\tvalid_0's l1: 0.492452\tvalid_0's binary_logloss: 0.681795\n",
      "[93]\tvalid_0's l1: 0.492416\tvalid_0's binary_logloss: 0.681787\n",
      "[94]\tvalid_0's l1: 0.492283\tvalid_0's binary_logloss: 0.681641\n",
      "[95]\tvalid_0's l1: 0.49228\tvalid_0's binary_logloss: 0.681639\n",
      "[96]\tvalid_0's l1: 0.49222\tvalid_0's binary_logloss: 0.681591\n",
      "[97]\tvalid_0's l1: 0.492154\tvalid_0's binary_logloss: 0.68153\n",
      "[98]\tvalid_0's l1: 0.492035\tvalid_0's binary_logloss: 0.681329\n",
      "[99]\tvalid_0's l1: 0.491933\tvalid_0's binary_logloss: 0.681271\n",
      "[100]\tvalid_0's l1: 0.491908\tvalid_0's binary_logloss: 0.681274\n",
      "Did not meet early stopping. Best iteration is:\n",
      "[100]\tvalid_0's l1: 0.491908\tvalid_0's binary_logloss: 0.681274\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1]\tvalid_0's l1: 0.501158\tvalid_0's binary_logloss: 0.696009\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501045\tvalid_0's binary_logloss: 0.695767\n",
      "[3]\tvalid_0's l1: 0.501061\tvalid_0's binary_logloss: 0.695775\n",
      "[4]\tvalid_0's l1: 0.500953\tvalid_0's binary_logloss: 0.695547\n",
      "[5]\tvalid_0's l1: 0.500969\tvalid_0's binary_logloss: 0.695568\n",
      "[6]\tvalid_0's l1: 0.500944\tvalid_0's binary_logloss: 0.695518\n",
      "[7]\tvalid_0's l1: 0.500817\tvalid_0's binary_logloss: 0.695262\n",
      "[8]\tvalid_0's l1: 0.500853\tvalid_0's binary_logloss: 0.695341\n",
      "[9]\tvalid_0's l1: 0.500873\tvalid_0's binary_logloss: 0.695392\n",
      "[10]\tvalid_0's l1: 0.500831\tvalid_0's binary_logloss: 0.695308\n",
      "[11]\tvalid_0's l1: 0.500815\tvalid_0's binary_logloss: 0.695299\n",
      "[12]\tvalid_0's l1: 0.500851\tvalid_0's binary_logloss: 0.695388\n",
      "Early stopping, best iteration is:\n",
      "[7]\tvalid_0's l1: 0.500817\tvalid_0's binary_logloss: 0.695262\n",
      "[1]\tvalid_0's l1: 0.501155\tvalid_0's binary_logloss: 0.696003\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501022\tvalid_0's binary_logloss: 0.695718\n",
      "[3]\tvalid_0's l1: 0.50089\tvalid_0's binary_logloss: 0.695449\n",
      "[4]\tvalid_0's l1: 0.50076\tvalid_0's binary_logloss: 0.695197\n",
      "[5]\tvalid_0's l1: 0.50063\tvalid_0's binary_logloss: 0.694961\n",
      "[6]\tvalid_0's l1: 0.500502\tvalid_0's binary_logloss: 0.69474\n",
      "[7]\tvalid_0's l1: 0.500482\tvalid_0's binary_logloss: 0.694732\n",
      "[8]\tvalid_0's l1: 0.500462\tvalid_0's binary_logloss: 0.694731\n",
      "[9]\tvalid_0's l1: 0.500441\tvalid_0's binary_logloss: 0.694735\n",
      "[10]\tvalid_0's l1: 0.500422\tvalid_0's binary_logloss: 0.694744\n",
      "[11]\tvalid_0's l1: 0.500402\tvalid_0's binary_logloss: 0.69476\n",
      "[12]\tvalid_0's l1: 0.500382\tvalid_0's binary_logloss: 0.69478\n",
      "[13]\tvalid_0's l1: 0.500363\tvalid_0's binary_logloss: 0.694806\n",
      "Early stopping, best iteration is:\n",
      "[8]\tvalid_0's l1: 0.500462\tvalid_0's binary_logloss: 0.694731\n",
      "[1]\tvalid_0's l1: 0.501149\tvalid_0's binary_logloss: 0.696022\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501007\tvalid_0's binary_logloss: 0.695745\n",
      "[3]\tvalid_0's l1: 0.500871\tvalid_0's binary_logloss: 0.695495\n",
      "[4]\tvalid_0's l1: 0.500774\tvalid_0's binary_logloss: 0.695296\n",
      "[5]\tvalid_0's l1: 0.500636\tvalid_0's binary_logloss: 0.695055\n",
      "[6]\tvalid_0's l1: 0.500541\tvalid_0's binary_logloss: 0.694882\n",
      "[7]\tvalid_0's l1: 0.500405\tvalid_0's binary_logloss: 0.694661\n",
      "[8]\tvalid_0's l1: 0.500311\tvalid_0's binary_logloss: 0.694513\n",
      "[9]\tvalid_0's l1: 0.500212\tvalid_0's binary_logloss: 0.69437\n",
      "[10]\tvalid_0's l1: 0.500079\tvalid_0's binary_logloss: 0.694176\n",
      "[11]\tvalid_0's l1: 0.499982\tvalid_0's binary_logloss: 0.694057\n",
      "[12]\tvalid_0's l1: 0.499884\tvalid_0's binary_logloss: 0.693953\n",
      "[13]\tvalid_0's l1: 0.49977\tvalid_0's binary_logloss: 0.693817\n",
      "[14]\tvalid_0's l1: 0.499681\tvalid_0's binary_logloss: 0.693747\n",
      "[15]\tvalid_0's l1: 0.499581\tvalid_0's binary_logloss: 0.69353\n",
      "[16]\tvalid_0's l1: 0.499468\tvalid_0's binary_logloss: 0.693425\n",
      "[17]\tvalid_0's l1: 0.499352\tvalid_0's binary_logloss: 0.693303\n",
      "[18]\tvalid_0's l1: 0.499246\tvalid_0's binary_logloss: 0.693232\n",
      "[19]\tvalid_0's l1: 0.49915\tvalid_0's binary_logloss: 0.69316\n",
      "[20]\tvalid_0's l1: 0.499135\tvalid_0's binary_logloss: 0.693231\n",
      "[21]\tvalid_0's l1: 0.499127\tvalid_0's binary_logloss: 0.693327\n",
      "[22]\tvalid_0's l1: 0.499006\tvalid_0's binary_logloss: 0.69309\n",
      "[23]\tvalid_0's l1: 0.498867\tvalid_0's binary_logloss: 0.692944\n",
      "[24]\tvalid_0's l1: 0.498829\tvalid_0's binary_logloss: 0.692995\n",
      "[25]\tvalid_0's l1: 0.498815\tvalid_0's binary_logloss: 0.693107\n",
      "[26]\tvalid_0's l1: 0.498696\tvalid_0's binary_logloss: 0.692889\n",
      "[27]\tvalid_0's l1: 0.49866\tvalid_0's binary_logloss: 0.692968\n",
      "[28]\tvalid_0's l1: 0.498565\tvalid_0's binary_logloss: 0.692925\n",
      "[29]\tvalid_0's l1: 0.498528\tvalid_0's binary_logloss: 0.693018\n",
      "[30]\tvalid_0's l1: 0.498515\tvalid_0's binary_logloss: 0.693168\n",
      "[31]\tvalid_0's l1: 0.498498\tvalid_0's binary_logloss: 0.693225\n",
      "Early stopping, best iteration is:\n",
      "[26]\tvalid_0's l1: 0.498696\tvalid_0's binary_logloss: 0.692889\n",
      "[1]\tvalid_0's l1: 0.50121\tvalid_0's binary_logloss: 0.696223\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501076\tvalid_0's binary_logloss: 0.695997\n",
      "[3]\tvalid_0's l1: 0.500942\tvalid_0's binary_logloss: 0.695784\n",
      "[4]\tvalid_0's l1: 0.500828\tvalid_0's binary_logloss: 0.695627\n",
      "[5]\tvalid_0's l1: 0.500744\tvalid_0's binary_logloss: 0.695523\n",
      "[6]\tvalid_0's l1: 0.500631\tvalid_0's binary_logloss: 0.69539\n",
      "[7]\tvalid_0's l1: 0.500565\tvalid_0's binary_logloss: 0.695353\n",
      "[8]\tvalid_0's l1: 0.500437\tvalid_0's binary_logloss: 0.695196\n",
      "[9]\tvalid_0's l1: 0.500356\tvalid_0's binary_logloss: 0.69513\n",
      "[10]\tvalid_0's l1: 0.500295\tvalid_0's binary_logloss: 0.695131\n",
      "[11]\tvalid_0's l1: 0.500202\tvalid_0's binary_logloss: 0.694949\n",
      "[12]\tvalid_0's l1: 0.50008\tvalid_0's binary_logloss: 0.694711\n",
      "[13]\tvalid_0's l1: 0.500004\tvalid_0's binary_logloss: 0.694679\n",
      "[14]\tvalid_0's l1: 0.499914\tvalid_0's binary_logloss: 0.694537\n",
      "[15]\tvalid_0's l1: 0.499728\tvalid_0's binary_logloss: 0.694166\n",
      "[16]\tvalid_0's l1: 0.499653\tvalid_0's binary_logloss: 0.694151\n",
      "[17]\tvalid_0's l1: 0.499498\tvalid_0's binary_logloss: 0.693874\n",
      "[18]\tvalid_0's l1: 0.499424\tvalid_0's binary_logloss: 0.693874\n",
      "[19]\tvalid_0's l1: 0.499337\tvalid_0's binary_logloss: 0.693781\n",
      "[20]\tvalid_0's l1: 0.499189\tvalid_0's binary_logloss: 0.693566\n",
      "[21]\tvalid_0's l1: 0.499009\tvalid_0's binary_logloss: 0.693259\n",
      "[22]\tvalid_0's l1: 0.498872\tvalid_0's binary_logloss: 0.693085\n",
      "[23]\tvalid_0's l1: 0.498723\tvalid_0's binary_logloss: 0.692869\n",
      "[24]\tvalid_0's l1: 0.498667\tvalid_0's binary_logloss: 0.692942\n",
      "[25]\tvalid_0's l1: 0.498491\tvalid_0's binary_logloss: 0.692679\n",
      "[26]\tvalid_0's l1: 0.498348\tvalid_0's binary_logloss: 0.692499\n",
      "[27]\tvalid_0's l1: 0.498224\tvalid_0's binary_logloss: 0.692366\n",
      "[28]\tvalid_0's l1: 0.49801\tvalid_0's binary_logloss: 0.692059\n",
      "[29]\tvalid_0's l1: 0.497867\tvalid_0's binary_logloss: 0.691898\n",
      "[30]\tvalid_0's l1: 0.49782\tvalid_0's binary_logloss: 0.69203\n",
      "[31]\tvalid_0's l1: 0.497712\tvalid_0's binary_logloss: 0.691957\n",
      "[32]\tvalid_0's l1: 0.497574\tvalid_0's binary_logloss: 0.691807\n",
      "[33]\tvalid_0's l1: 0.497455\tvalid_0's binary_logloss: 0.69172\n",
      "[34]\tvalid_0's l1: 0.497349\tvalid_0's binary_logloss: 0.691647\n",
      "[35]\tvalid_0's l1: 0.497212\tvalid_0's binary_logloss: 0.69151\n",
      "[36]\tvalid_0's l1: 0.497167\tvalid_0's binary_logloss: 0.691669\n",
      "[37]\tvalid_0's l1: 0.497031\tvalid_0's binary_logloss: 0.691564\n",
      "[38]\tvalid_0's l1: 0.496825\tvalid_0's binary_logloss: 0.691305\n",
      "[39]\tvalid_0's l1: 0.496711\tvalid_0's binary_logloss: 0.691258\n",
      "[40]\tvalid_0's l1: 0.49662\tvalid_0's binary_logloss: 0.691185\n",
      "[41]\tvalid_0's l1: 0.496464\tvalid_0's binary_logloss: 0.69103\n",
      "[42]\tvalid_0's l1: 0.49642\tvalid_0's binary_logloss: 0.691212\n",
      "[43]\tvalid_0's l1: 0.496283\tvalid_0's binary_logloss: 0.691126\n",
      "[44]\tvalid_0's l1: 0.496152\tvalid_0's binary_logloss: 0.691067\n",
      "[45]\tvalid_0's l1: 0.495992\tvalid_0's binary_logloss: 0.690933\n",
      "[46]\tvalid_0's l1: 0.495858\tvalid_0's binary_logloss: 0.690874\n",
      "[47]\tvalid_0's l1: 0.495866\tvalid_0's binary_logloss: 0.69107\n",
      "[48]\tvalid_0's l1: 0.49569\tvalid_0's binary_logloss: 0.690862\n",
      "[49]\tvalid_0's l1: 0.495563\tvalid_0's binary_logloss: 0.690777\n",
      "[50]\tvalid_0's l1: 0.495476\tvalid_0's binary_logloss: 0.690724\n",
      "[51]\tvalid_0's l1: 0.495469\tvalid_0's binary_logloss: 0.690933\n",
      "[52]\tvalid_0's l1: 0.49532\tvalid_0's binary_logloss: 0.69086\n",
      "[53]\tvalid_0's l1: 0.495172\tvalid_0's binary_logloss: 0.690745\n",
      "[54]\tvalid_0's l1: 0.495087\tvalid_0's binary_logloss: 0.690698\n",
      "[55]\tvalid_0's l1: 0.495002\tvalid_0's binary_logloss: 0.690656\n",
      "[56]\tvalid_0's l1: 0.494786\tvalid_0's binary_logloss: 0.690417\n",
      "[57]\tvalid_0's l1: 0.494702\tvalid_0's binary_logloss: 0.690381\n",
      "[58]\tvalid_0's l1: 0.494696\tvalid_0's binary_logloss: 0.690602\n",
      "[59]\tvalid_0's l1: 0.494567\tvalid_0's binary_logloss: 0.690553\n",
      "[60]\tvalid_0's l1: 0.494465\tvalid_0's binary_logloss: 0.690479\n",
      "[61]\tvalid_0's l1: 0.494383\tvalid_0's binary_logloss: 0.690451\n",
      "[62]\tvalid_0's l1: 0.494247\tvalid_0's binary_logloss: 0.690308\n",
      "[63]\tvalid_0's l1: 0.494165\tvalid_0's binary_logloss: 0.690285\n",
      "[64]\tvalid_0's l1: 0.494038\tvalid_0's binary_logloss: 0.690172\n",
      "[65]\tvalid_0's l1: 0.493985\tvalid_0's binary_logloss: 0.690192\n",
      "[66]\tvalid_0's l1: 0.493881\tvalid_0's binary_logloss: 0.690116\n",
      "[67]\tvalid_0's l1: 0.493902\tvalid_0's binary_logloss: 0.690384\n",
      "[68]\tvalid_0's l1: 0.493756\tvalid_0's binary_logloss: 0.690291\n",
      "[69]\tvalid_0's l1: 0.493607\tvalid_0's binary_logloss: 0.690123\n",
      "[70]\tvalid_0's l1: 0.493628\tvalid_0's binary_logloss: 0.690401\n",
      "[71]\tvalid_0's l1: 0.493481\tvalid_0's binary_logloss: 0.690244\n",
      "Early stopping, best iteration is:\n",
      "[66]\tvalid_0's l1: 0.493881\tvalid_0's binary_logloss: 0.690116\n",
      "[1]\tvalid_0's l1: 0.501228\tvalid_0's binary_logloss: 0.696199\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501127\tvalid_0's binary_logloss: 0.695984\n",
      "[3]\tvalid_0's l1: 0.500967\tvalid_0's binary_logloss: 0.695633\n",
      "[4]\tvalid_0's l1: 0.500868\tvalid_0's binary_logloss: 0.695427\n",
      "[5]\tvalid_0's l1: 0.50071\tvalid_0's binary_logloss: 0.695087\n",
      "[6]\tvalid_0's l1: 0.500613\tvalid_0's binary_logloss: 0.69489\n",
      "[7]\tvalid_0's l1: 0.50038\tvalid_0's binary_logloss: 0.694409\n",
      "[8]\tvalid_0's l1: 0.500284\tvalid_0's binary_logloss: 0.69422\n",
      "[9]\tvalid_0's l1: 0.500054\tvalid_0's binary_logloss: 0.693754\n",
      "[10]\tvalid_0's l1: 0.49996\tvalid_0's binary_logloss: 0.693573\n",
      "[11]\tvalid_0's l1: 0.499807\tvalid_0's binary_logloss: 0.693253\n",
      "[12]\tvalid_0's l1: 0.49958\tvalid_0's binary_logloss: 0.692806\n",
      "[13]\tvalid_0's l1: 0.499488\tvalid_0's binary_logloss: 0.692615\n",
      "[14]\tvalid_0's l1: 0.499337\tvalid_0's binary_logloss: 0.692307\n",
      "[15]\tvalid_0's l1: 0.499246\tvalid_0's binary_logloss: 0.692143\n",
      "[16]\tvalid_0's l1: 0.499025\tvalid_0's binary_logloss: 0.691717\n",
      "[17]\tvalid_0's l1: 0.498936\tvalid_0's binary_logloss: 0.69156\n",
      "[18]\tvalid_0's l1: 0.498717\tvalid_0's binary_logloss: 0.691148\n",
      "[19]\tvalid_0's l1: 0.498633\tvalid_0's binary_logloss: 0.690986\n",
      "[20]\tvalid_0's l1: 0.498511\tvalid_0's binary_logloss: 0.69074\n",
      "[21]\tvalid_0's l1: 0.498425\tvalid_0's binary_logloss: 0.690594\n",
      "[22]\tvalid_0's l1: 0.498384\tvalid_0's binary_logloss: 0.690514\n",
      "[23]\tvalid_0's l1: 0.498311\tvalid_0's binary_logloss: 0.690368\n",
      "[24]\tvalid_0's l1: 0.498235\tvalid_0's binary_logloss: 0.690197\n",
      "[25]\tvalid_0's l1: 0.498183\tvalid_0's binary_logloss: 0.690102\n",
      "[26]\tvalid_0's l1: 0.498123\tvalid_0's binary_logloss: 0.689981\n",
      "[27]\tvalid_0's l1: 0.498048\tvalid_0's binary_logloss: 0.689817\n",
      "[28]\tvalid_0's l1: 0.497917\tvalid_0's binary_logloss: 0.689591\n",
      "[29]\tvalid_0's l1: 0.497846\tvalid_0's binary_logloss: 0.689455\n",
      "[30]\tvalid_0's l1: 0.497716\tvalid_0's binary_logloss: 0.689239\n",
      "[31]\tvalid_0's l1: 0.497642\tvalid_0's binary_logloss: 0.68908\n",
      "[32]\tvalid_0's l1: 0.497548\tvalid_0's binary_logloss: 0.688929\n",
      "[33]\tvalid_0's l1: 0.49742\tvalid_0's binary_logloss: 0.688723\n",
      "[34]\tvalid_0's l1: 0.497327\tvalid_0's binary_logloss: 0.688577\n",
      "[35]\tvalid_0's l1: 0.4972\tvalid_0's binary_logloss: 0.688382\n",
      "[36]\tvalid_0's l1: 0.497136\tvalid_0's binary_logloss: 0.6883\n",
      "[37]\tvalid_0's l1: 0.49701\tvalid_0's binary_logloss: 0.688115\n",
      "[38]\tvalid_0's l1: 0.496934\tvalid_0's binary_logloss: 0.687958\n",
      "[39]\tvalid_0's l1: 0.496844\tvalid_0's binary_logloss: 0.687821\n",
      "[40]\tvalid_0's l1: 0.496736\tvalid_0's binary_logloss: 0.687617\n",
      "[41]\tvalid_0's l1: 0.496612\tvalid_0's binary_logloss: 0.687442\n",
      "[42]\tvalid_0's l1: 0.496549\tvalid_0's binary_logloss: 0.687369\n",
      "[43]\tvalid_0's l1: 0.496393\tvalid_0's binary_logloss: 0.687107\n",
      "[44]\tvalid_0's l1: 0.496304\tvalid_0's binary_logloss: 0.686979\n",
      "[45]\tvalid_0's l1: 0.496275\tvalid_0's binary_logloss: 0.686964\n",
      "[46]\tvalid_0's l1: 0.496154\tvalid_0's binary_logloss: 0.686807\n",
      "[47]\tvalid_0's l1: 0.496091\tvalid_0's binary_logloss: 0.686651\n",
      "[48]\tvalid_0's l1: 0.49603\tvalid_0's binary_logloss: 0.686587\n",
      "[49]\tvalid_0's l1: 0.495877\tvalid_0's binary_logloss: 0.686339\n",
      "[50]\tvalid_0's l1: 0.495815\tvalid_0's binary_logloss: 0.686184\n",
      "[51]\tvalid_0's l1: 0.495728\tvalid_0's binary_logloss: 0.686067\n",
      "[52]\tvalid_0's l1: 0.495576\tvalid_0's binary_logloss: 0.685827\n",
      "[53]\tvalid_0's l1: 0.495562\tvalid_0's binary_logloss: 0.685827\n",
      "[54]\tvalid_0's l1: 0.495445\tvalid_0's binary_logloss: 0.68569\n",
      "[55]\tvalid_0's l1: 0.495309\tvalid_0's binary_logloss: 0.685424\n",
      "[56]\tvalid_0's l1: 0.495238\tvalid_0's binary_logloss: 0.685338\n",
      "[57]\tvalid_0's l1: 0.495224\tvalid_0's binary_logloss: 0.685343\n",
      "[58]\tvalid_0's l1: 0.495076\tvalid_0's binary_logloss: 0.685117\n",
      "[59]\tvalid_0's l1: 0.494943\tvalid_0's binary_logloss: 0.684859\n",
      "[60]\tvalid_0's l1: 0.494828\tvalid_0's binary_logloss: 0.684736\n",
      "[61]\tvalid_0's l1: 0.494696\tvalid_0's binary_logloss: 0.684485\n",
      "[62]\tvalid_0's l1: 0.494624\tvalid_0's binary_logloss: 0.684395\n",
      "[63]\tvalid_0's l1: 0.494611\tvalid_0's binary_logloss: 0.684402\n",
      "[64]\tvalid_0's l1: 0.494465\tvalid_0's binary_logloss: 0.684192\n",
      "[65]\tvalid_0's l1: 0.494335\tvalid_0's binary_logloss: 0.68395\n",
      "[66]\tvalid_0's l1: 0.494223\tvalid_0's binary_logloss: 0.683838\n",
      "[67]\tvalid_0's l1: 0.494154\tvalid_0's binary_logloss: 0.683762\n",
      "[68]\tvalid_0's l1: 0.494026\tvalid_0's binary_logloss: 0.683527\n",
      "[69]\tvalid_0's l1: 0.494013\tvalid_0's binary_logloss: 0.683536\n",
      "[70]\tvalid_0's l1: 0.493902\tvalid_0's binary_logloss: 0.683431\n",
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      "[73]\tvalid_0's l1: 0.493688\tvalid_0's binary_logloss: 0.683157\n",
      "[74]\tvalid_0's l1: 0.493673\tvalid_0's binary_logloss: 0.68317\n",
      "[75]\tvalid_0's l1: 0.493547\tvalid_0's binary_logloss: 0.682944\n",
      "[76]\tvalid_0's l1: 0.493439\tvalid_0's binary_logloss: 0.682851\n",
      "[77]\tvalid_0's l1: 0.493372\tvalid_0's binary_logloss: 0.682783\n",
      "[78]\tvalid_0's l1: 0.493369\tvalid_0's binary_logloss: 0.682779\n",
      "[79]\tvalid_0's l1: 0.493337\tvalid_0's binary_logloss: 0.68276\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[80]\tvalid_0's l1: 0.493199\tvalid_0's binary_logloss: 0.682583\n",
      "[81]\tvalid_0's l1: 0.493075\tvalid_0's binary_logloss: 0.682365\n",
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      "[85]\tvalid_0's l1: 0.492861\tvalid_0's binary_logloss: 0.68219\n",
      "[86]\tvalid_0's l1: 0.492825\tvalid_0's binary_logloss: 0.682176\n",
      "[87]\tvalid_0's l1: 0.492759\tvalid_0's binary_logloss: 0.682115\n",
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      "[93]\tvalid_0's l1: 0.492416\tvalid_0's binary_logloss: 0.681787\n",
      "[94]\tvalid_0's l1: 0.492283\tvalid_0's binary_logloss: 0.681641\n",
      "[95]\tvalid_0's l1: 0.49228\tvalid_0's binary_logloss: 0.681639\n",
      "[96]\tvalid_0's l1: 0.49222\tvalid_0's binary_logloss: 0.681591\n",
      "[97]\tvalid_0's l1: 0.492154\tvalid_0's binary_logloss: 0.68153\n",
      "[98]\tvalid_0's l1: 0.492035\tvalid_0's binary_logloss: 0.681329\n",
      "[99]\tvalid_0's l1: 0.491933\tvalid_0's binary_logloss: 0.681271\n",
      "[100]\tvalid_0's l1: 0.491908\tvalid_0's binary_logloss: 0.681274\n",
      "Did not meet early stopping. Best iteration is:\n",
      "[100]\tvalid_0's l1: 0.491908\tvalid_0's binary_logloss: 0.681274\n",
      "[1]\tvalid_0's l1: 0.501158\tvalid_0's binary_logloss: 0.696009\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501045\tvalid_0's binary_logloss: 0.695767\n",
      "[3]\tvalid_0's l1: 0.501061\tvalid_0's binary_logloss: 0.695775\n",
      "[4]\tvalid_0's l1: 0.500953\tvalid_0's binary_logloss: 0.695547\n",
      "[5]\tvalid_0's l1: 0.500969\tvalid_0's binary_logloss: 0.695568\n",
      "[6]\tvalid_0's l1: 0.500944\tvalid_0's binary_logloss: 0.695518\n",
      "[7]\tvalid_0's l1: 0.500817\tvalid_0's binary_logloss: 0.695262\n",
      "[8]\tvalid_0's l1: 0.500853\tvalid_0's binary_logloss: 0.695341\n",
      "[9]\tvalid_0's l1: 0.500873\tvalid_0's binary_logloss: 0.695392\n",
      "[10]\tvalid_0's l1: 0.500831\tvalid_0's binary_logloss: 0.695308\n",
      "[11]\tvalid_0's l1: 0.500815\tvalid_0's binary_logloss: 0.695299\n",
      "[12]\tvalid_0's l1: 0.500851\tvalid_0's binary_logloss: 0.695388\n",
      "Early stopping, best iteration is:\n",
      "[7]\tvalid_0's l1: 0.500817\tvalid_0's binary_logloss: 0.695262\n",
      "[1]\tvalid_0's l1: 0.501155\tvalid_0's binary_logloss: 0.696003\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501022\tvalid_0's binary_logloss: 0.695718\n",
      "[3]\tvalid_0's l1: 0.50089\tvalid_0's binary_logloss: 0.695449\n",
      "[4]\tvalid_0's l1: 0.50076\tvalid_0's binary_logloss: 0.695197\n",
      "[5]\tvalid_0's l1: 0.50063\tvalid_0's binary_logloss: 0.694961\n",
      "[6]\tvalid_0's l1: 0.500502\tvalid_0's binary_logloss: 0.69474\n",
      "[7]\tvalid_0's l1: 0.500482\tvalid_0's binary_logloss: 0.694732\n",
      "[8]\tvalid_0's l1: 0.500462\tvalid_0's binary_logloss: 0.694731\n",
      "[9]\tvalid_0's l1: 0.500441\tvalid_0's binary_logloss: 0.694735\n",
      "[10]\tvalid_0's l1: 0.500422\tvalid_0's binary_logloss: 0.694744\n",
      "[11]\tvalid_0's l1: 0.500402\tvalid_0's binary_logloss: 0.69476\n",
      "[12]\tvalid_0's l1: 0.500382\tvalid_0's binary_logloss: 0.69478\n",
      "[13]\tvalid_0's l1: 0.500363\tvalid_0's binary_logloss: 0.694806\n",
      "Early stopping, best iteration is:\n",
      "[8]\tvalid_0's l1: 0.500462\tvalid_0's binary_logloss: 0.694731\n",
      "[1]\tvalid_0's l1: 0.501149\tvalid_0's binary_logloss: 0.696022\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501007\tvalid_0's binary_logloss: 0.695745\n",
      "[3]\tvalid_0's l1: 0.500871\tvalid_0's binary_logloss: 0.695495\n",
      "[4]\tvalid_0's l1: 0.500774\tvalid_0's binary_logloss: 0.695296\n",
      "[5]\tvalid_0's l1: 0.500636\tvalid_0's binary_logloss: 0.695055\n",
      "[6]\tvalid_0's l1: 0.500541\tvalid_0's binary_logloss: 0.694882\n",
      "[7]\tvalid_0's l1: 0.500405\tvalid_0's binary_logloss: 0.694661\n",
      "[8]\tvalid_0's l1: 0.500311\tvalid_0's binary_logloss: 0.694513\n",
      "[9]\tvalid_0's l1: 0.500212\tvalid_0's binary_logloss: 0.69437\n",
      "[10]\tvalid_0's l1: 0.500079\tvalid_0's binary_logloss: 0.694176\n",
      "[11]\tvalid_0's l1: 0.499982\tvalid_0's binary_logloss: 0.694057\n",
      "[12]\tvalid_0's l1: 0.499884\tvalid_0's binary_logloss: 0.693953\n",
      "[13]\tvalid_0's l1: 0.49977\tvalid_0's binary_logloss: 0.693817\n",
      "[14]\tvalid_0's l1: 0.499681\tvalid_0's binary_logloss: 0.693747\n",
      "[15]\tvalid_0's l1: 0.499581\tvalid_0's binary_logloss: 0.69353\n",
      "[16]\tvalid_0's l1: 0.499468\tvalid_0's binary_logloss: 0.693425\n",
      "[17]\tvalid_0's l1: 0.499352\tvalid_0's binary_logloss: 0.693303\n",
      "[18]\tvalid_0's l1: 0.499246\tvalid_0's binary_logloss: 0.693232\n",
      "[19]\tvalid_0's l1: 0.49915\tvalid_0's binary_logloss: 0.69316\n",
      "[20]\tvalid_0's l1: 0.499135\tvalid_0's binary_logloss: 0.693231\n",
      "[21]\tvalid_0's l1: 0.499127\tvalid_0's binary_logloss: 0.693327\n",
      "[22]\tvalid_0's l1: 0.499006\tvalid_0's binary_logloss: 0.69309\n",
      "[23]\tvalid_0's l1: 0.498867\tvalid_0's binary_logloss: 0.692944\n",
      "[24]\tvalid_0's l1: 0.498829\tvalid_0's binary_logloss: 0.692995\n",
      "[25]\tvalid_0's l1: 0.498815\tvalid_0's binary_logloss: 0.693107\n",
      "[26]\tvalid_0's l1: 0.498696\tvalid_0's binary_logloss: 0.692889\n",
      "[27]\tvalid_0's l1: 0.49866\tvalid_0's binary_logloss: 0.692968\n",
      "[28]\tvalid_0's l1: 0.498565\tvalid_0's binary_logloss: 0.692925\n",
      "[29]\tvalid_0's l1: 0.498528\tvalid_0's binary_logloss: 0.693018\n",
      "[30]\tvalid_0's l1: 0.498515\tvalid_0's binary_logloss: 0.693168\n",
      "[31]\tvalid_0's l1: 0.498498\tvalid_0's binary_logloss: 0.693225\n",
      "Early stopping, best iteration is:\n",
      "[26]\tvalid_0's l1: 0.498696\tvalid_0's binary_logloss: 0.692889\n",
      "[1]\tvalid_0's l1: 0.50121\tvalid_0's binary_logloss: 0.696223\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501076\tvalid_0's binary_logloss: 0.695997\n",
      "[3]\tvalid_0's l1: 0.500942\tvalid_0's binary_logloss: 0.695784\n",
      "[4]\tvalid_0's l1: 0.500828\tvalid_0's binary_logloss: 0.695627\n",
      "[5]\tvalid_0's l1: 0.500744\tvalid_0's binary_logloss: 0.695523\n",
      "[6]\tvalid_0's l1: 0.500631\tvalid_0's binary_logloss: 0.69539\n",
      "[7]\tvalid_0's l1: 0.500565\tvalid_0's binary_logloss: 0.695353\n",
      "[8]\tvalid_0's l1: 0.500437\tvalid_0's binary_logloss: 0.695196\n",
      "[9]\tvalid_0's l1: 0.500356\tvalid_0's binary_logloss: 0.69513\n",
      "[10]\tvalid_0's l1: 0.500295\tvalid_0's binary_logloss: 0.695131\n",
      "[11]\tvalid_0's l1: 0.500202\tvalid_0's binary_logloss: 0.694949\n",
      "[12]\tvalid_0's l1: 0.50008\tvalid_0's binary_logloss: 0.694711\n",
      "[13]\tvalid_0's l1: 0.500004\tvalid_0's binary_logloss: 0.694679\n",
      "[14]\tvalid_0's l1: 0.499914\tvalid_0's binary_logloss: 0.694537\n",
      "[15]\tvalid_0's l1: 0.499728\tvalid_0's binary_logloss: 0.694166\n",
      "[16]\tvalid_0's l1: 0.499653\tvalid_0's binary_logloss: 0.694151\n",
      "[17]\tvalid_0's l1: 0.499498\tvalid_0's binary_logloss: 0.693874\n",
      "[18]\tvalid_0's l1: 0.499424\tvalid_0's binary_logloss: 0.693874\n",
      "[19]\tvalid_0's l1: 0.499337\tvalid_0's binary_logloss: 0.693781\n",
      "[20]\tvalid_0's l1: 0.499189\tvalid_0's binary_logloss: 0.693566\n",
      "[21]\tvalid_0's l1: 0.499009\tvalid_0's binary_logloss: 0.693259\n",
      "[22]\tvalid_0's l1: 0.498872\tvalid_0's binary_logloss: 0.693085\n",
      "[23]\tvalid_0's l1: 0.498723\tvalid_0's binary_logloss: 0.692869\n",
      "[24]\tvalid_0's l1: 0.498667\tvalid_0's binary_logloss: 0.692942\n",
      "[25]\tvalid_0's l1: 0.498491\tvalid_0's binary_logloss: 0.692679\n",
      "[26]\tvalid_0's l1: 0.498348\tvalid_0's binary_logloss: 0.692499\n",
      "[27]\tvalid_0's l1: 0.498224\tvalid_0's binary_logloss: 0.692366\n",
      "[28]\tvalid_0's l1: 0.49801\tvalid_0's binary_logloss: 0.692059\n",
      "[29]\tvalid_0's l1: 0.497867\tvalid_0's binary_logloss: 0.691898\n",
      "[30]\tvalid_0's l1: 0.49782\tvalid_0's binary_logloss: 0.69203\n",
      "[31]\tvalid_0's l1: 0.497712\tvalid_0's binary_logloss: 0.691957\n",
      "[32]\tvalid_0's l1: 0.497574\tvalid_0's binary_logloss: 0.691807\n",
      "[33]\tvalid_0's l1: 0.497455\tvalid_0's binary_logloss: 0.69172\n",
      "[34]\tvalid_0's l1: 0.497349\tvalid_0's binary_logloss: 0.691647\n",
      "[35]\tvalid_0's l1: 0.497212\tvalid_0's binary_logloss: 0.69151\n",
      "[36]\tvalid_0's l1: 0.497167\tvalid_0's binary_logloss: 0.691669\n",
      "[37]\tvalid_0's l1: 0.497031\tvalid_0's binary_logloss: 0.691564\n",
      "[38]\tvalid_0's l1: 0.496825\tvalid_0's binary_logloss: 0.691305\n",
      "[39]\tvalid_0's l1: 0.496711\tvalid_0's binary_logloss: 0.691258\n",
      "[40]\tvalid_0's l1: 0.49662\tvalid_0's binary_logloss: 0.691185\n",
      "[41]\tvalid_0's l1: 0.496464\tvalid_0's binary_logloss: 0.69103\n",
      "[42]\tvalid_0's l1: 0.49642\tvalid_0's binary_logloss: 0.691212\n",
      "[43]\tvalid_0's l1: 0.496283\tvalid_0's binary_logloss: 0.691126\n",
      "[44]\tvalid_0's l1: 0.496152\tvalid_0's binary_logloss: 0.691067\n",
      "[45]\tvalid_0's l1: 0.495992\tvalid_0's binary_logloss: 0.690933\n",
      "[46]\tvalid_0's l1: 0.495858\tvalid_0's binary_logloss: 0.690874\n",
      "[47]\tvalid_0's l1: 0.495866\tvalid_0's binary_logloss: 0.69107\n",
      "[48]\tvalid_0's l1: 0.49569\tvalid_0's binary_logloss: 0.690862\n",
      "[49]\tvalid_0's l1: 0.495563\tvalid_0's binary_logloss: 0.690777\n",
      "[50]\tvalid_0's l1: 0.495476\tvalid_0's binary_logloss: 0.690724\n",
      "[51]\tvalid_0's l1: 0.495469\tvalid_0's binary_logloss: 0.690933\n",
      "[52]\tvalid_0's l1: 0.49532\tvalid_0's binary_logloss: 0.69086\n",
      "[53]\tvalid_0's l1: 0.495172\tvalid_0's binary_logloss: 0.690745\n",
      "[54]\tvalid_0's l1: 0.495087\tvalid_0's binary_logloss: 0.690698\n",
      "[55]\tvalid_0's l1: 0.495002\tvalid_0's binary_logloss: 0.690656\n",
      "[56]\tvalid_0's l1: 0.494786\tvalid_0's binary_logloss: 0.690417\n",
      "[57]\tvalid_0's l1: 0.494702\tvalid_0's binary_logloss: 0.690381\n",
      "[58]\tvalid_0's l1: 0.494696\tvalid_0's binary_logloss: 0.690602\n",
      "[59]\tvalid_0's l1: 0.494567\tvalid_0's binary_logloss: 0.690553\n",
      "[60]\tvalid_0's l1: 0.494465\tvalid_0's binary_logloss: 0.690479\n",
      "[61]\tvalid_0's l1: 0.494383\tvalid_0's binary_logloss: 0.690451\n",
      "[62]\tvalid_0's l1: 0.494247\tvalid_0's binary_logloss: 0.690308\n",
      "[63]\tvalid_0's l1: 0.494165\tvalid_0's binary_logloss: 0.690285\n",
      "[64]\tvalid_0's l1: 0.494038\tvalid_0's binary_logloss: 0.690172\n",
      "[65]\tvalid_0's l1: 0.493985\tvalid_0's binary_logloss: 0.690192\n",
      "[66]\tvalid_0's l1: 0.493881\tvalid_0's binary_logloss: 0.690116\n",
      "[67]\tvalid_0's l1: 0.493902\tvalid_0's binary_logloss: 0.690384\n",
      "[68]\tvalid_0's l1: 0.493756\tvalid_0's binary_logloss: 0.690291\n",
      "[69]\tvalid_0's l1: 0.493607\tvalid_0's binary_logloss: 0.690123\n",
      "[70]\tvalid_0's l1: 0.493628\tvalid_0's binary_logloss: 0.690401\n",
      "[71]\tvalid_0's l1: 0.493481\tvalid_0's binary_logloss: 0.690244\n",
      "Early stopping, best iteration is:\n",
      "[66]\tvalid_0's l1: 0.493881\tvalid_0's binary_logloss: 0.690116\n",
      "[1]\tvalid_0's l1: 0.501228\tvalid_0's binary_logloss: 0.696199\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501127\tvalid_0's binary_logloss: 0.695984\n",
      "[3]\tvalid_0's l1: 0.500967\tvalid_0's binary_logloss: 0.695633\n",
      "[4]\tvalid_0's l1: 0.500868\tvalid_0's binary_logloss: 0.695427\n",
      "[5]\tvalid_0's l1: 0.50071\tvalid_0's binary_logloss: 0.695087\n",
      "[6]\tvalid_0's l1: 0.500613\tvalid_0's binary_logloss: 0.69489\n",
      "[7]\tvalid_0's l1: 0.50038\tvalid_0's binary_logloss: 0.694409\n",
      "[8]\tvalid_0's l1: 0.500284\tvalid_0's binary_logloss: 0.69422\n",
      "[9]\tvalid_0's l1: 0.500054\tvalid_0's binary_logloss: 0.693754\n",
      "[10]\tvalid_0's l1: 0.49996\tvalid_0's binary_logloss: 0.693573\n",
      "[11]\tvalid_0's l1: 0.499807\tvalid_0's binary_logloss: 0.693253\n",
      "[12]\tvalid_0's l1: 0.49958\tvalid_0's binary_logloss: 0.692806\n",
      "[13]\tvalid_0's l1: 0.499488\tvalid_0's binary_logloss: 0.692615\n",
      "[14]\tvalid_0's l1: 0.499337\tvalid_0's binary_logloss: 0.692307\n",
      "[15]\tvalid_0's l1: 0.499246\tvalid_0's binary_logloss: 0.692143\n",
      "[16]\tvalid_0's l1: 0.499025\tvalid_0's binary_logloss: 0.691717\n",
      "[17]\tvalid_0's l1: 0.498936\tvalid_0's binary_logloss: 0.69156\n",
      "[18]\tvalid_0's l1: 0.498717\tvalid_0's binary_logloss: 0.691148\n",
      "[19]\tvalid_0's l1: 0.498633\tvalid_0's binary_logloss: 0.690986\n",
      "[20]\tvalid_0's l1: 0.498511\tvalid_0's binary_logloss: 0.69074\n",
      "[21]\tvalid_0's l1: 0.498425\tvalid_0's binary_logloss: 0.690594\n",
      "[22]\tvalid_0's l1: 0.498384\tvalid_0's binary_logloss: 0.690514\n",
      "[23]\tvalid_0's l1: 0.498311\tvalid_0's binary_logloss: 0.690368\n",
      "[24]\tvalid_0's l1: 0.498235\tvalid_0's binary_logloss: 0.690197\n",
      "[25]\tvalid_0's l1: 0.498183\tvalid_0's binary_logloss: 0.690102\n",
      "[26]\tvalid_0's l1: 0.498123\tvalid_0's binary_logloss: 0.689981\n",
      "[27]\tvalid_0's l1: 0.498048\tvalid_0's binary_logloss: 0.689817\n",
      "[28]\tvalid_0's l1: 0.497917\tvalid_0's binary_logloss: 0.689591\n",
      "[29]\tvalid_0's l1: 0.497846\tvalid_0's binary_logloss: 0.689455\n",
      "[30]\tvalid_0's l1: 0.497716\tvalid_0's binary_logloss: 0.689239\n",
      "[31]\tvalid_0's l1: 0.497642\tvalid_0's binary_logloss: 0.68908\n",
      "[32]\tvalid_0's l1: 0.497548\tvalid_0's binary_logloss: 0.688929\n",
      "[33]\tvalid_0's l1: 0.49742\tvalid_0's binary_logloss: 0.688723\n",
      "[34]\tvalid_0's l1: 0.497327\tvalid_0's binary_logloss: 0.688577\n",
      "[35]\tvalid_0's l1: 0.4972\tvalid_0's binary_logloss: 0.688382\n",
      "[36]\tvalid_0's l1: 0.497136\tvalid_0's binary_logloss: 0.6883\n",
      "[37]\tvalid_0's l1: 0.49701\tvalid_0's binary_logloss: 0.688115\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[38]\tvalid_0's l1: 0.496934\tvalid_0's binary_logloss: 0.687958\n",
      "[39]\tvalid_0's l1: 0.496844\tvalid_0's binary_logloss: 0.687821\n",
      "[40]\tvalid_0's l1: 0.496736\tvalid_0's binary_logloss: 0.687617\n",
      "[41]\tvalid_0's l1: 0.496612\tvalid_0's binary_logloss: 0.687442\n",
      "[42]\tvalid_0's l1: 0.496549\tvalid_0's binary_logloss: 0.687369\n",
      "[43]\tvalid_0's l1: 0.496393\tvalid_0's binary_logloss: 0.687107\n",
      "[44]\tvalid_0's l1: 0.496304\tvalid_0's binary_logloss: 0.686979\n",
      "[45]\tvalid_0's l1: 0.496275\tvalid_0's binary_logloss: 0.686964\n",
      "[46]\tvalid_0's l1: 0.496154\tvalid_0's binary_logloss: 0.686807\n",
      "[47]\tvalid_0's l1: 0.496091\tvalid_0's binary_logloss: 0.686651\n",
      "[48]\tvalid_0's l1: 0.49603\tvalid_0's binary_logloss: 0.686587\n",
      "[49]\tvalid_0's l1: 0.495877\tvalid_0's binary_logloss: 0.686339\n",
      "[50]\tvalid_0's l1: 0.495815\tvalid_0's binary_logloss: 0.686184\n",
      "[51]\tvalid_0's l1: 0.495728\tvalid_0's binary_logloss: 0.686067\n",
      "[52]\tvalid_0's l1: 0.495576\tvalid_0's binary_logloss: 0.685827\n",
      "[53]\tvalid_0's l1: 0.495562\tvalid_0's binary_logloss: 0.685827\n",
      "[54]\tvalid_0's l1: 0.495445\tvalid_0's binary_logloss: 0.68569\n",
      "[55]\tvalid_0's l1: 0.495309\tvalid_0's binary_logloss: 0.685424\n",
      "[56]\tvalid_0's l1: 0.495238\tvalid_0's binary_logloss: 0.685338\n",
      "[57]\tvalid_0's l1: 0.495224\tvalid_0's binary_logloss: 0.685343\n",
      "[58]\tvalid_0's l1: 0.495076\tvalid_0's binary_logloss: 0.685117\n",
      "[59]\tvalid_0's l1: 0.494943\tvalid_0's binary_logloss: 0.684859\n",
      "[60]\tvalid_0's l1: 0.494828\tvalid_0's binary_logloss: 0.684736\n",
      "[61]\tvalid_0's l1: 0.494696\tvalid_0's binary_logloss: 0.684485\n",
      "[62]\tvalid_0's l1: 0.494624\tvalid_0's binary_logloss: 0.684395\n",
      "[63]\tvalid_0's l1: 0.494611\tvalid_0's binary_logloss: 0.684402\n",
      "[64]\tvalid_0's l1: 0.494465\tvalid_0's binary_logloss: 0.684192\n",
      "[65]\tvalid_0's l1: 0.494335\tvalid_0's binary_logloss: 0.68395\n",
      "[66]\tvalid_0's l1: 0.494223\tvalid_0's binary_logloss: 0.683838\n",
      "[67]\tvalid_0's l1: 0.494154\tvalid_0's binary_logloss: 0.683762\n",
      "[68]\tvalid_0's l1: 0.494026\tvalid_0's binary_logloss: 0.683527\n",
      "[69]\tvalid_0's l1: 0.494013\tvalid_0's binary_logloss: 0.683536\n",
      "[70]\tvalid_0's l1: 0.493902\tvalid_0's binary_logloss: 0.683431\n",
      "[71]\tvalid_0's l1: 0.493898\tvalid_0's binary_logloss: 0.683426\n",
      "[72]\tvalid_0's l1: 0.493757\tvalid_0's binary_logloss: 0.683237\n",
      "[73]\tvalid_0's l1: 0.493688\tvalid_0's binary_logloss: 0.683157\n",
      "[74]\tvalid_0's l1: 0.493673\tvalid_0's binary_logloss: 0.68317\n",
      "[75]\tvalid_0's l1: 0.493547\tvalid_0's binary_logloss: 0.682944\n",
      "[76]\tvalid_0's l1: 0.493439\tvalid_0's binary_logloss: 0.682851\n",
      "[77]\tvalid_0's l1: 0.493372\tvalid_0's binary_logloss: 0.682783\n",
      "[78]\tvalid_0's l1: 0.493369\tvalid_0's binary_logloss: 0.682779\n",
      "[79]\tvalid_0's l1: 0.493337\tvalid_0's binary_logloss: 0.68276\n",
      "[80]\tvalid_0's l1: 0.493199\tvalid_0's binary_logloss: 0.682583\n",
      "[81]\tvalid_0's l1: 0.493075\tvalid_0's binary_logloss: 0.682365\n",
      "[82]\tvalid_0's l1: 0.493038\tvalid_0's binary_logloss: 0.682344\n",
      "[83]\tvalid_0's l1: 0.492932\tvalid_0's binary_logloss: 0.682264\n",
      "[84]\tvalid_0's l1: 0.492864\tvalid_0's binary_logloss: 0.682194\n",
      "[85]\tvalid_0's l1: 0.492861\tvalid_0's binary_logloss: 0.68219\n",
      "[86]\tvalid_0's l1: 0.492825\tvalid_0's binary_logloss: 0.682176\n",
      "[87]\tvalid_0's l1: 0.492759\tvalid_0's binary_logloss: 0.682115\n",
      "[88]\tvalid_0's l1: 0.492637\tvalid_0's binary_logloss: 0.681903\n",
      "[89]\tvalid_0's l1: 0.492593\tvalid_0's binary_logloss: 0.681932\n",
      "[90]\tvalid_0's l1: 0.492519\tvalid_0's binary_logloss: 0.681856\n",
      "[91]\tvalid_0's l1: 0.492516\tvalid_0's binary_logloss: 0.681853\n",
      "[92]\tvalid_0's l1: 0.492452\tvalid_0's binary_logloss: 0.681795\n",
      "[93]\tvalid_0's l1: 0.492416\tvalid_0's binary_logloss: 0.681787\n",
      "[94]\tvalid_0's l1: 0.492283\tvalid_0's binary_logloss: 0.681641\n",
      "[95]\tvalid_0's l1: 0.49228\tvalid_0's binary_logloss: 0.681639\n",
      "[96]\tvalid_0's l1: 0.49222\tvalid_0's binary_logloss: 0.681591\n",
      "[97]\tvalid_0's l1: 0.492154\tvalid_0's binary_logloss: 0.68153\n",
      "[98]\tvalid_0's l1: 0.492035\tvalid_0's binary_logloss: 0.681329\n",
      "[99]\tvalid_0's l1: 0.491933\tvalid_0's binary_logloss: 0.681271\n",
      "[100]\tvalid_0's l1: 0.491908\tvalid_0's binary_logloss: 0.681274\n",
      "Did not meet early stopping. Best iteration is:\n",
      "[100]\tvalid_0's l1: 0.491908\tvalid_0's binary_logloss: 0.681274\n",
      "[1]\tvalid_0's l1: 0.501158\tvalid_0's binary_logloss: 0.696009\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501045\tvalid_0's binary_logloss: 0.695767\n",
      "[3]\tvalid_0's l1: 0.501061\tvalid_0's binary_logloss: 0.695775\n",
      "[4]\tvalid_0's l1: 0.500953\tvalid_0's binary_logloss: 0.695547\n",
      "[5]\tvalid_0's l1: 0.500969\tvalid_0's binary_logloss: 0.695568\n",
      "[6]\tvalid_0's l1: 0.500944\tvalid_0's binary_logloss: 0.695518\n",
      "[7]\tvalid_0's l1: 0.500817\tvalid_0's binary_logloss: 0.695262\n",
      "[8]\tvalid_0's l1: 0.500853\tvalid_0's binary_logloss: 0.695341\n",
      "[9]\tvalid_0's l1: 0.500873\tvalid_0's binary_logloss: 0.695392\n",
      "[10]\tvalid_0's l1: 0.500831\tvalid_0's binary_logloss: 0.695308\n",
      "[11]\tvalid_0's l1: 0.500815\tvalid_0's binary_logloss: 0.695299\n",
      "[12]\tvalid_0's l1: 0.500851\tvalid_0's binary_logloss: 0.695388\n",
      "Early stopping, best iteration is:\n",
      "[7]\tvalid_0's l1: 0.500817\tvalid_0's binary_logloss: 0.695262\n",
      "[1]\tvalid_0's l1: 0.501155\tvalid_0's binary_logloss: 0.696003\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501022\tvalid_0's binary_logloss: 0.695718\n",
      "[3]\tvalid_0's l1: 0.50089\tvalid_0's binary_logloss: 0.695449\n",
      "[4]\tvalid_0's l1: 0.50076\tvalid_0's binary_logloss: 0.695197\n",
      "[5]\tvalid_0's l1: 0.50063\tvalid_0's binary_logloss: 0.694961\n",
      "[6]\tvalid_0's l1: 0.500502\tvalid_0's binary_logloss: 0.69474\n",
      "[7]\tvalid_0's l1: 0.500482\tvalid_0's binary_logloss: 0.694732\n",
      "[8]\tvalid_0's l1: 0.500462\tvalid_0's binary_logloss: 0.694731\n",
      "[9]\tvalid_0's l1: 0.500441\tvalid_0's binary_logloss: 0.694735\n",
      "[10]\tvalid_0's l1: 0.500422\tvalid_0's binary_logloss: 0.694744\n",
      "[11]\tvalid_0's l1: 0.500402\tvalid_0's binary_logloss: 0.69476\n",
      "[12]\tvalid_0's l1: 0.500382\tvalid_0's binary_logloss: 0.69478\n",
      "[13]\tvalid_0's l1: 0.500363\tvalid_0's binary_logloss: 0.694806\n",
      "Early stopping, best iteration is:\n",
      "[8]\tvalid_0's l1: 0.500462\tvalid_0's binary_logloss: 0.694731\n",
      "[1]\tvalid_0's l1: 0.501149\tvalid_0's binary_logloss: 0.696022\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501007\tvalid_0's binary_logloss: 0.695745\n",
      "[3]\tvalid_0's l1: 0.500871\tvalid_0's binary_logloss: 0.695495\n",
      "[4]\tvalid_0's l1: 0.500774\tvalid_0's binary_logloss: 0.695296\n",
      "[5]\tvalid_0's l1: 0.500636\tvalid_0's binary_logloss: 0.695055\n",
      "[6]\tvalid_0's l1: 0.500541\tvalid_0's binary_logloss: 0.694882\n",
      "[7]\tvalid_0's l1: 0.500405\tvalid_0's binary_logloss: 0.694661\n",
      "[8]\tvalid_0's l1: 0.500311\tvalid_0's binary_logloss: 0.694513\n",
      "[9]\tvalid_0's l1: 0.500212\tvalid_0's binary_logloss: 0.69437\n",
      "[10]\tvalid_0's l1: 0.500079\tvalid_0's binary_logloss: 0.694176\n",
      "[11]\tvalid_0's l1: 0.499982\tvalid_0's binary_logloss: 0.694057\n",
      "[12]\tvalid_0's l1: 0.499884\tvalid_0's binary_logloss: 0.693953\n",
      "[13]\tvalid_0's l1: 0.49977\tvalid_0's binary_logloss: 0.693817\n",
      "[14]\tvalid_0's l1: 0.499681\tvalid_0's binary_logloss: 0.693747\n",
      "[15]\tvalid_0's l1: 0.499581\tvalid_0's binary_logloss: 0.69353\n",
      "[16]\tvalid_0's l1: 0.499468\tvalid_0's binary_logloss: 0.693425\n",
      "[17]\tvalid_0's l1: 0.499352\tvalid_0's binary_logloss: 0.693303\n",
      "[18]\tvalid_0's l1: 0.499246\tvalid_0's binary_logloss: 0.693232\n",
      "[19]\tvalid_0's l1: 0.49915\tvalid_0's binary_logloss: 0.69316\n",
      "[20]\tvalid_0's l1: 0.499135\tvalid_0's binary_logloss: 0.693231\n",
      "[21]\tvalid_0's l1: 0.499127\tvalid_0's binary_logloss: 0.693327\n",
      "[22]\tvalid_0's l1: 0.499006\tvalid_0's binary_logloss: 0.69309\n",
      "[23]\tvalid_0's l1: 0.498867\tvalid_0's binary_logloss: 0.692944\n",
      "[24]\tvalid_0's l1: 0.498829\tvalid_0's binary_logloss: 0.692995\n",
      "[25]\tvalid_0's l1: 0.498815\tvalid_0's binary_logloss: 0.693107\n",
      "[26]\tvalid_0's l1: 0.498696\tvalid_0's binary_logloss: 0.692889\n",
      "[27]\tvalid_0's l1: 0.49866\tvalid_0's binary_logloss: 0.692968\n",
      "[28]\tvalid_0's l1: 0.498565\tvalid_0's binary_logloss: 0.692925\n",
      "[29]\tvalid_0's l1: 0.498528\tvalid_0's binary_logloss: 0.693018\n",
      "[30]\tvalid_0's l1: 0.498515\tvalid_0's binary_logloss: 0.693168\n",
      "[31]\tvalid_0's l1: 0.498498\tvalid_0's binary_logloss: 0.693225\n",
      "Early stopping, best iteration is:\n",
      "[26]\tvalid_0's l1: 0.498696\tvalid_0's binary_logloss: 0.692889\n",
      "[1]\tvalid_0's l1: 0.50121\tvalid_0's binary_logloss: 0.696223\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501076\tvalid_0's binary_logloss: 0.695997\n",
      "[3]\tvalid_0's l1: 0.500942\tvalid_0's binary_logloss: 0.695784\n",
      "[4]\tvalid_0's l1: 0.500828\tvalid_0's binary_logloss: 0.695627\n",
      "[5]\tvalid_0's l1: 0.500744\tvalid_0's binary_logloss: 0.695523\n",
      "[6]\tvalid_0's l1: 0.500631\tvalid_0's binary_logloss: 0.69539\n",
      "[7]\tvalid_0's l1: 0.500565\tvalid_0's binary_logloss: 0.695353\n",
      "[8]\tvalid_0's l1: 0.500437\tvalid_0's binary_logloss: 0.695196\n",
      "[9]\tvalid_0's l1: 0.500356\tvalid_0's binary_logloss: 0.69513\n",
      "[10]\tvalid_0's l1: 0.500295\tvalid_0's binary_logloss: 0.695131\n",
      "[11]\tvalid_0's l1: 0.500202\tvalid_0's binary_logloss: 0.694949\n",
      "[12]\tvalid_0's l1: 0.50008\tvalid_0's binary_logloss: 0.694711\n",
      "[13]\tvalid_0's l1: 0.500004\tvalid_0's binary_logloss: 0.694679\n",
      "[14]\tvalid_0's l1: 0.499914\tvalid_0's binary_logloss: 0.694537\n",
      "[15]\tvalid_0's l1: 0.499728\tvalid_0's binary_logloss: 0.694166\n",
      "[16]\tvalid_0's l1: 0.499653\tvalid_0's binary_logloss: 0.694151\n",
      "[17]\tvalid_0's l1: 0.499498\tvalid_0's binary_logloss: 0.693874\n",
      "[18]\tvalid_0's l1: 0.499424\tvalid_0's binary_logloss: 0.693874\n",
      "[19]\tvalid_0's l1: 0.499337\tvalid_0's binary_logloss: 0.693781\n",
      "[20]\tvalid_0's l1: 0.499189\tvalid_0's binary_logloss: 0.693566\n",
      "[21]\tvalid_0's l1: 0.499009\tvalid_0's binary_logloss: 0.693259\n",
      "[22]\tvalid_0's l1: 0.498872\tvalid_0's binary_logloss: 0.693085\n",
      "[23]\tvalid_0's l1: 0.498723\tvalid_0's binary_logloss: 0.692869\n",
      "[24]\tvalid_0's l1: 0.498667\tvalid_0's binary_logloss: 0.692942\n",
      "[25]\tvalid_0's l1: 0.498491\tvalid_0's binary_logloss: 0.692679\n",
      "[26]\tvalid_0's l1: 0.498348\tvalid_0's binary_logloss: 0.692499\n",
      "[27]\tvalid_0's l1: 0.498224\tvalid_0's binary_logloss: 0.692366\n",
      "[28]\tvalid_0's l1: 0.49801\tvalid_0's binary_logloss: 0.692059\n",
      "[29]\tvalid_0's l1: 0.497867\tvalid_0's binary_logloss: 0.691898\n",
      "[30]\tvalid_0's l1: 0.49782\tvalid_0's binary_logloss: 0.69203\n",
      "[31]\tvalid_0's l1: 0.497712\tvalid_0's binary_logloss: 0.691957\n",
      "[32]\tvalid_0's l1: 0.497574\tvalid_0's binary_logloss: 0.691807\n",
      "[33]\tvalid_0's l1: 0.497455\tvalid_0's binary_logloss: 0.69172\n",
      "[34]\tvalid_0's l1: 0.497349\tvalid_0's binary_logloss: 0.691647\n",
      "[35]\tvalid_0's l1: 0.497212\tvalid_0's binary_logloss: 0.69151\n",
      "[36]\tvalid_0's l1: 0.497167\tvalid_0's binary_logloss: 0.691669\n",
      "[37]\tvalid_0's l1: 0.497031\tvalid_0's binary_logloss: 0.691564\n",
      "[38]\tvalid_0's l1: 0.496825\tvalid_0's binary_logloss: 0.691305\n",
      "[39]\tvalid_0's l1: 0.496711\tvalid_0's binary_logloss: 0.691258\n",
      "[40]\tvalid_0's l1: 0.49662\tvalid_0's binary_logloss: 0.691185\n",
      "[41]\tvalid_0's l1: 0.496464\tvalid_0's binary_logloss: 0.69103\n",
      "[42]\tvalid_0's l1: 0.49642\tvalid_0's binary_logloss: 0.691212\n",
      "[43]\tvalid_0's l1: 0.496283\tvalid_0's binary_logloss: 0.691126\n",
      "[44]\tvalid_0's l1: 0.496152\tvalid_0's binary_logloss: 0.691067\n",
      "[45]\tvalid_0's l1: 0.495992\tvalid_0's binary_logloss: 0.690933\n",
      "[46]\tvalid_0's l1: 0.495858\tvalid_0's binary_logloss: 0.690874\n",
      "[47]\tvalid_0's l1: 0.495866\tvalid_0's binary_logloss: 0.69107\n",
      "[48]\tvalid_0's l1: 0.49569\tvalid_0's binary_logloss: 0.690862\n",
      "[49]\tvalid_0's l1: 0.495563\tvalid_0's binary_logloss: 0.690777\n",
      "[50]\tvalid_0's l1: 0.495476\tvalid_0's binary_logloss: 0.690724\n",
      "[51]\tvalid_0's l1: 0.495469\tvalid_0's binary_logloss: 0.690933\n",
      "[52]\tvalid_0's l1: 0.49532\tvalid_0's binary_logloss: 0.69086\n",
      "[53]\tvalid_0's l1: 0.495172\tvalid_0's binary_logloss: 0.690745\n",
      "[54]\tvalid_0's l1: 0.495087\tvalid_0's binary_logloss: 0.690698\n",
      "[55]\tvalid_0's l1: 0.495002\tvalid_0's binary_logloss: 0.690656\n",
      "[56]\tvalid_0's l1: 0.494786\tvalid_0's binary_logloss: 0.690417\n",
      "[57]\tvalid_0's l1: 0.494702\tvalid_0's binary_logloss: 0.690381\n",
      "[58]\tvalid_0's l1: 0.494696\tvalid_0's binary_logloss: 0.690602\n",
      "[59]\tvalid_0's l1: 0.494567\tvalid_0's binary_logloss: 0.690553\n",
      "[60]\tvalid_0's l1: 0.494465\tvalid_0's binary_logloss: 0.690479\n",
      "[61]\tvalid_0's l1: 0.494383\tvalid_0's binary_logloss: 0.690451\n",
      "[62]\tvalid_0's l1: 0.494247\tvalid_0's binary_logloss: 0.690308\n",
      "[63]\tvalid_0's l1: 0.494165\tvalid_0's binary_logloss: 0.690285\n",
      "[64]\tvalid_0's l1: 0.494038\tvalid_0's binary_logloss: 0.690172\n",
      "[65]\tvalid_0's l1: 0.493985\tvalid_0's binary_logloss: 0.690192\n",
      "[66]\tvalid_0's l1: 0.493881\tvalid_0's binary_logloss: 0.690116\n",
      "[67]\tvalid_0's l1: 0.493902\tvalid_0's binary_logloss: 0.690384\n",
      "[68]\tvalid_0's l1: 0.493756\tvalid_0's binary_logloss: 0.690291\n",
      "[69]\tvalid_0's l1: 0.493607\tvalid_0's binary_logloss: 0.690123\n",
      "[70]\tvalid_0's l1: 0.493628\tvalid_0's binary_logloss: 0.690401\n",
      "[71]\tvalid_0's l1: 0.493481\tvalid_0's binary_logloss: 0.690244\n",
      "Early stopping, best iteration is:\n",
      "[66]\tvalid_0's l1: 0.493881\tvalid_0's binary_logloss: 0.690116\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1]\tvalid_0's l1: 0.501228\tvalid_0's binary_logloss: 0.696199\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501127\tvalid_0's binary_logloss: 0.695984\n",
      "[3]\tvalid_0's l1: 0.500967\tvalid_0's binary_logloss: 0.695633\n",
      "[4]\tvalid_0's l1: 0.500868\tvalid_0's binary_logloss: 0.695427\n",
      "[5]\tvalid_0's l1: 0.50071\tvalid_0's binary_logloss: 0.695087\n",
      "[6]\tvalid_0's l1: 0.500613\tvalid_0's binary_logloss: 0.69489\n",
      "[7]\tvalid_0's l1: 0.50038\tvalid_0's binary_logloss: 0.694409\n",
      "[8]\tvalid_0's l1: 0.500284\tvalid_0's binary_logloss: 0.69422\n",
      "[9]\tvalid_0's l1: 0.500054\tvalid_0's binary_logloss: 0.693754\n",
      "[10]\tvalid_0's l1: 0.49996\tvalid_0's binary_logloss: 0.693573\n",
      "[11]\tvalid_0's l1: 0.499807\tvalid_0's binary_logloss: 0.693253\n",
      "[12]\tvalid_0's l1: 0.49958\tvalid_0's binary_logloss: 0.692806\n",
      "[13]\tvalid_0's l1: 0.499488\tvalid_0's binary_logloss: 0.692615\n",
      "[14]\tvalid_0's l1: 0.499337\tvalid_0's binary_logloss: 0.692307\n",
      "[15]\tvalid_0's l1: 0.499246\tvalid_0's binary_logloss: 0.692143\n",
      "[16]\tvalid_0's l1: 0.499025\tvalid_0's binary_logloss: 0.691717\n",
      "[17]\tvalid_0's l1: 0.498936\tvalid_0's binary_logloss: 0.69156\n",
      "[18]\tvalid_0's l1: 0.498717\tvalid_0's binary_logloss: 0.691148\n",
      "[19]\tvalid_0's l1: 0.498633\tvalid_0's binary_logloss: 0.690986\n",
      "[20]\tvalid_0's l1: 0.498511\tvalid_0's binary_logloss: 0.69074\n",
      "[21]\tvalid_0's l1: 0.498425\tvalid_0's binary_logloss: 0.690594\n",
      "[22]\tvalid_0's l1: 0.498384\tvalid_0's binary_logloss: 0.690514\n",
      "[23]\tvalid_0's l1: 0.498311\tvalid_0's binary_logloss: 0.690368\n",
      "[24]\tvalid_0's l1: 0.498235\tvalid_0's binary_logloss: 0.690197\n",
      "[25]\tvalid_0's l1: 0.498183\tvalid_0's binary_logloss: 0.690102\n",
      "[26]\tvalid_0's l1: 0.498123\tvalid_0's binary_logloss: 0.689981\n",
      "[27]\tvalid_0's l1: 0.498048\tvalid_0's binary_logloss: 0.689817\n",
      "[28]\tvalid_0's l1: 0.497917\tvalid_0's binary_logloss: 0.689591\n",
      "[29]\tvalid_0's l1: 0.497846\tvalid_0's binary_logloss: 0.689455\n",
      "[30]\tvalid_0's l1: 0.497716\tvalid_0's binary_logloss: 0.689239\n",
      "[31]\tvalid_0's l1: 0.497642\tvalid_0's binary_logloss: 0.68908\n",
      "[32]\tvalid_0's l1: 0.497548\tvalid_0's binary_logloss: 0.688929\n",
      "[33]\tvalid_0's l1: 0.49742\tvalid_0's binary_logloss: 0.688723\n",
      "[34]\tvalid_0's l1: 0.497327\tvalid_0's binary_logloss: 0.688577\n",
      "[35]\tvalid_0's l1: 0.4972\tvalid_0's binary_logloss: 0.688382\n",
      "[36]\tvalid_0's l1: 0.497136\tvalid_0's binary_logloss: 0.6883\n",
      "[37]\tvalid_0's l1: 0.49701\tvalid_0's binary_logloss: 0.688115\n",
      "[38]\tvalid_0's l1: 0.496934\tvalid_0's binary_logloss: 0.687958\n",
      "[39]\tvalid_0's l1: 0.496844\tvalid_0's binary_logloss: 0.687821\n",
      "[40]\tvalid_0's l1: 0.496736\tvalid_0's binary_logloss: 0.687617\n",
      "[41]\tvalid_0's l1: 0.496612\tvalid_0's binary_logloss: 0.687442\n",
      "[42]\tvalid_0's l1: 0.496549\tvalid_0's binary_logloss: 0.687369\n",
      "[43]\tvalid_0's l1: 0.496393\tvalid_0's binary_logloss: 0.687107\n",
      "[44]\tvalid_0's l1: 0.496304\tvalid_0's binary_logloss: 0.686979\n",
      "[45]\tvalid_0's l1: 0.496275\tvalid_0's binary_logloss: 0.686964\n",
      "[46]\tvalid_0's l1: 0.496154\tvalid_0's binary_logloss: 0.686807\n",
      "[47]\tvalid_0's l1: 0.496091\tvalid_0's binary_logloss: 0.686651\n",
      "[48]\tvalid_0's l1: 0.49603\tvalid_0's binary_logloss: 0.686587\n",
      "[49]\tvalid_0's l1: 0.495877\tvalid_0's binary_logloss: 0.686339\n",
      "[50]\tvalid_0's l1: 0.495815\tvalid_0's binary_logloss: 0.686184\n",
      "[51]\tvalid_0's l1: 0.495728\tvalid_0's binary_logloss: 0.686067\n",
      "[52]\tvalid_0's l1: 0.495576\tvalid_0's binary_logloss: 0.685827\n",
      "[53]\tvalid_0's l1: 0.495562\tvalid_0's binary_logloss: 0.685827\n",
      "[54]\tvalid_0's l1: 0.495445\tvalid_0's binary_logloss: 0.68569\n",
      "[55]\tvalid_0's l1: 0.495309\tvalid_0's binary_logloss: 0.685424\n",
      "[56]\tvalid_0's l1: 0.495238\tvalid_0's binary_logloss: 0.685338\n",
      "[57]\tvalid_0's l1: 0.495224\tvalid_0's binary_logloss: 0.685343\n",
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      "[216]\tvalid_0's l1: 0.484075\tvalid_0's binary_logloss: 0.672388\n",
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      "[218]\tvalid_0's l1: 0.483978\tvalid_0's binary_logloss: 0.672187\n",
      "[219]\tvalid_0's l1: 0.483984\tvalid_0's binary_logloss: 0.672242\n",
      "[220]\tvalid_0's l1: 0.483975\tvalid_0's binary_logloss: 0.672351\n",
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      "[223]\tvalid_0's l1: 0.483884\tvalid_0's binary_logloss: 0.672242\n",
      "Early stopping, best iteration is:\n",
      "[218]\tvalid_0's l1: 0.483978\tvalid_0's binary_logloss: 0.672187\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1]\tvalid_0's l1: 0.501158\tvalid_0's binary_logloss: 0.696009\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501045\tvalid_0's binary_logloss: 0.695767\n",
      "[3]\tvalid_0's l1: 0.501061\tvalid_0's binary_logloss: 0.695775\n",
      "[4]\tvalid_0's l1: 0.500953\tvalid_0's binary_logloss: 0.695547\n",
      "[5]\tvalid_0's l1: 0.500969\tvalid_0's binary_logloss: 0.695568\n",
      "[6]\tvalid_0's l1: 0.500944\tvalid_0's binary_logloss: 0.695518\n",
      "[7]\tvalid_0's l1: 0.500817\tvalid_0's binary_logloss: 0.695262\n",
      "[8]\tvalid_0's l1: 0.500853\tvalid_0's binary_logloss: 0.695341\n",
      "[9]\tvalid_0's l1: 0.500873\tvalid_0's binary_logloss: 0.695392\n",
      "[10]\tvalid_0's l1: 0.500831\tvalid_0's binary_logloss: 0.695308\n",
      "[11]\tvalid_0's l1: 0.500815\tvalid_0's binary_logloss: 0.695299\n",
      "[12]\tvalid_0's l1: 0.500851\tvalid_0's binary_logloss: 0.695388\n",
      "Early stopping, best iteration is:\n",
      "[7]\tvalid_0's l1: 0.500817\tvalid_0's binary_logloss: 0.695262\n",
      "[1]\tvalid_0's l1: 0.501155\tvalid_0's binary_logloss: 0.696003\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501022\tvalid_0's binary_logloss: 0.695718\n",
      "[3]\tvalid_0's l1: 0.50089\tvalid_0's binary_logloss: 0.695449\n",
      "[4]\tvalid_0's l1: 0.50076\tvalid_0's binary_logloss: 0.695197\n",
      "[5]\tvalid_0's l1: 0.50063\tvalid_0's binary_logloss: 0.694961\n",
      "[6]\tvalid_0's l1: 0.500502\tvalid_0's binary_logloss: 0.69474\n",
      "[7]\tvalid_0's l1: 0.500482\tvalid_0's binary_logloss: 0.694732\n",
      "[8]\tvalid_0's l1: 0.500462\tvalid_0's binary_logloss: 0.694731\n",
      "[9]\tvalid_0's l1: 0.500441\tvalid_0's binary_logloss: 0.694735\n",
      "[10]\tvalid_0's l1: 0.500422\tvalid_0's binary_logloss: 0.694744\n",
      "[11]\tvalid_0's l1: 0.500402\tvalid_0's binary_logloss: 0.69476\n",
      "[12]\tvalid_0's l1: 0.500382\tvalid_0's binary_logloss: 0.69478\n",
      "[13]\tvalid_0's l1: 0.500363\tvalid_0's binary_logloss: 0.694806\n",
      "Early stopping, best iteration is:\n",
      "[8]\tvalid_0's l1: 0.500462\tvalid_0's binary_logloss: 0.694731\n",
      "[1]\tvalid_0's l1: 0.501149\tvalid_0's binary_logloss: 0.696022\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501007\tvalid_0's binary_logloss: 0.695745\n",
      "[3]\tvalid_0's l1: 0.500871\tvalid_0's binary_logloss: 0.695495\n",
      "[4]\tvalid_0's l1: 0.500774\tvalid_0's binary_logloss: 0.695296\n",
      "[5]\tvalid_0's l1: 0.500636\tvalid_0's binary_logloss: 0.695055\n",
      "[6]\tvalid_0's l1: 0.500541\tvalid_0's binary_logloss: 0.694882\n",
      "[7]\tvalid_0's l1: 0.500405\tvalid_0's binary_logloss: 0.694661\n",
      "[8]\tvalid_0's l1: 0.500311\tvalid_0's binary_logloss: 0.694513\n",
      "[9]\tvalid_0's l1: 0.500212\tvalid_0's binary_logloss: 0.69437\n",
      "[10]\tvalid_0's l1: 0.500079\tvalid_0's binary_logloss: 0.694176\n",
      "[11]\tvalid_0's l1: 0.499982\tvalid_0's binary_logloss: 0.694057\n",
      "[12]\tvalid_0's l1: 0.499884\tvalid_0's binary_logloss: 0.693953\n",
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      "[14]\tvalid_0's l1: 0.499681\tvalid_0's binary_logloss: 0.693747\n",
      "[15]\tvalid_0's l1: 0.499581\tvalid_0's binary_logloss: 0.69353\n",
      "[16]\tvalid_0's l1: 0.499468\tvalid_0's binary_logloss: 0.693425\n",
      "[17]\tvalid_0's l1: 0.499352\tvalid_0's binary_logloss: 0.693303\n",
      "[18]\tvalid_0's l1: 0.499246\tvalid_0's binary_logloss: 0.693232\n",
      "[19]\tvalid_0's l1: 0.49915\tvalid_0's binary_logloss: 0.69316\n",
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      "[21]\tvalid_0's l1: 0.499127\tvalid_0's binary_logloss: 0.693327\n",
      "[22]\tvalid_0's l1: 0.499006\tvalid_0's binary_logloss: 0.69309\n",
      "[23]\tvalid_0's l1: 0.498867\tvalid_0's binary_logloss: 0.692944\n",
      "[24]\tvalid_0's l1: 0.498829\tvalid_0's binary_logloss: 0.692995\n",
      "[25]\tvalid_0's l1: 0.498815\tvalid_0's binary_logloss: 0.693107\n",
      "[26]\tvalid_0's l1: 0.498696\tvalid_0's binary_logloss: 0.692889\n",
      "[27]\tvalid_0's l1: 0.49866\tvalid_0's binary_logloss: 0.692968\n",
      "[28]\tvalid_0's l1: 0.498565\tvalid_0's binary_logloss: 0.692925\n",
      "[29]\tvalid_0's l1: 0.498528\tvalid_0's binary_logloss: 0.693018\n",
      "[30]\tvalid_0's l1: 0.498515\tvalid_0's binary_logloss: 0.693168\n",
      "[31]\tvalid_0's l1: 0.498498\tvalid_0's binary_logloss: 0.693225\n",
      "Early stopping, best iteration is:\n",
      "[26]\tvalid_0's l1: 0.498696\tvalid_0's binary_logloss: 0.692889\n",
      "[1]\tvalid_0's l1: 0.50121\tvalid_0's binary_logloss: 0.696223\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501076\tvalid_0's binary_logloss: 0.695997\n",
      "[3]\tvalid_0's l1: 0.500942\tvalid_0's binary_logloss: 0.695784\n",
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      "[7]\tvalid_0's l1: 0.500565\tvalid_0's binary_logloss: 0.695353\n",
      "[8]\tvalid_0's l1: 0.500437\tvalid_0's binary_logloss: 0.695196\n",
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      "[10]\tvalid_0's l1: 0.500295\tvalid_0's binary_logloss: 0.695131\n",
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      "[12]\tvalid_0's l1: 0.50008\tvalid_0's binary_logloss: 0.694711\n",
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      "[14]\tvalid_0's l1: 0.499914\tvalid_0's binary_logloss: 0.694537\n",
      "[15]\tvalid_0's l1: 0.499728\tvalid_0's binary_logloss: 0.694166\n",
      "[16]\tvalid_0's l1: 0.499653\tvalid_0's binary_logloss: 0.694151\n",
      "[17]\tvalid_0's l1: 0.499498\tvalid_0's binary_logloss: 0.693874\n",
      "[18]\tvalid_0's l1: 0.499424\tvalid_0's binary_logloss: 0.693874\n",
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      "[38]\tvalid_0's l1: 0.496825\tvalid_0's binary_logloss: 0.691305\n",
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      "[44]\tvalid_0's l1: 0.496152\tvalid_0's binary_logloss: 0.691067\n",
      "[45]\tvalid_0's l1: 0.495992\tvalid_0's binary_logloss: 0.690933\n",
      "[46]\tvalid_0's l1: 0.495858\tvalid_0's binary_logloss: 0.690874\n",
      "[47]\tvalid_0's l1: 0.495866\tvalid_0's binary_logloss: 0.69107\n",
      "[48]\tvalid_0's l1: 0.49569\tvalid_0's binary_logloss: 0.690862\n",
      "[49]\tvalid_0's l1: 0.495563\tvalid_0's binary_logloss: 0.690777\n",
      "[50]\tvalid_0's l1: 0.495476\tvalid_0's binary_logloss: 0.690724\n",
      "[51]\tvalid_0's l1: 0.495469\tvalid_0's binary_logloss: 0.690933\n",
      "[52]\tvalid_0's l1: 0.49532\tvalid_0's binary_logloss: 0.69086\n",
      "[53]\tvalid_0's l1: 0.495172\tvalid_0's binary_logloss: 0.690745\n",
      "[54]\tvalid_0's l1: 0.495087\tvalid_0's binary_logloss: 0.690698\n",
      "[55]\tvalid_0's l1: 0.495002\tvalid_0's binary_logloss: 0.690656\n",
      "[56]\tvalid_0's l1: 0.494786\tvalid_0's binary_logloss: 0.690417\n",
      "[57]\tvalid_0's l1: 0.494702\tvalid_0's binary_logloss: 0.690381\n",
      "[58]\tvalid_0's l1: 0.494696\tvalid_0's binary_logloss: 0.690602\n",
      "[59]\tvalid_0's l1: 0.494567\tvalid_0's binary_logloss: 0.690553\n",
      "[60]\tvalid_0's l1: 0.494465\tvalid_0's binary_logloss: 0.690479\n",
      "[61]\tvalid_0's l1: 0.494383\tvalid_0's binary_logloss: 0.690451\n",
      "[62]\tvalid_0's l1: 0.494247\tvalid_0's binary_logloss: 0.690308\n",
      "[63]\tvalid_0's l1: 0.494165\tvalid_0's binary_logloss: 0.690285\n",
      "[64]\tvalid_0's l1: 0.494038\tvalid_0's binary_logloss: 0.690172\n",
      "[65]\tvalid_0's l1: 0.493985\tvalid_0's binary_logloss: 0.690192\n",
      "[66]\tvalid_0's l1: 0.493881\tvalid_0's binary_logloss: 0.690116\n",
      "[67]\tvalid_0's l1: 0.493902\tvalid_0's binary_logloss: 0.690384\n",
      "[68]\tvalid_0's l1: 0.493756\tvalid_0's binary_logloss: 0.690291\n",
      "[69]\tvalid_0's l1: 0.493607\tvalid_0's binary_logloss: 0.690123\n",
      "[70]\tvalid_0's l1: 0.493628\tvalid_0's binary_logloss: 0.690401\n",
      "[71]\tvalid_0's l1: 0.493481\tvalid_0's binary_logloss: 0.690244\n",
      "Early stopping, best iteration is:\n",
      "[66]\tvalid_0's l1: 0.493881\tvalid_0's binary_logloss: 0.690116\n",
      "[1]\tvalid_0's l1: 0.501228\tvalid_0's binary_logloss: 0.696199\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501127\tvalid_0's binary_logloss: 0.695984\n",
      "[3]\tvalid_0's l1: 0.500967\tvalid_0's binary_logloss: 0.695633\n",
      "[4]\tvalid_0's l1: 0.500868\tvalid_0's binary_logloss: 0.695427\n",
      "[5]\tvalid_0's l1: 0.50071\tvalid_0's binary_logloss: 0.695087\n",
      "[6]\tvalid_0's l1: 0.500613\tvalid_0's binary_logloss: 0.69489\n",
      "[7]\tvalid_0's l1: 0.50038\tvalid_0's binary_logloss: 0.694409\n",
      "[8]\tvalid_0's l1: 0.500284\tvalid_0's binary_logloss: 0.69422\n",
      "[9]\tvalid_0's l1: 0.500054\tvalid_0's binary_logloss: 0.693754\n",
      "[10]\tvalid_0's l1: 0.49996\tvalid_0's binary_logloss: 0.693573\n",
      "[11]\tvalid_0's l1: 0.499807\tvalid_0's binary_logloss: 0.693253\n",
      "[12]\tvalid_0's l1: 0.49958\tvalid_0's binary_logloss: 0.692806\n",
      "[13]\tvalid_0's l1: 0.499488\tvalid_0's binary_logloss: 0.692615\n",
      "[14]\tvalid_0's l1: 0.499337\tvalid_0's binary_logloss: 0.692307\n",
      "[15]\tvalid_0's l1: 0.499246\tvalid_0's binary_logloss: 0.692143\n",
      "[16]\tvalid_0's l1: 0.499025\tvalid_0's binary_logloss: 0.691717\n",
      "[17]\tvalid_0's l1: 0.498936\tvalid_0's binary_logloss: 0.69156\n",
      "[18]\tvalid_0's l1: 0.498717\tvalid_0's binary_logloss: 0.691148\n",
      "[19]\tvalid_0's l1: 0.498633\tvalid_0's binary_logloss: 0.690986\n",
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      "[24]\tvalid_0's l1: 0.498235\tvalid_0's binary_logloss: 0.690197\n",
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      "[33]\tvalid_0's l1: 0.49742\tvalid_0's binary_logloss: 0.688723\n",
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      "[35]\tvalid_0's l1: 0.4972\tvalid_0's binary_logloss: 0.688382\n",
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      "[37]\tvalid_0's l1: 0.49701\tvalid_0's binary_logloss: 0.688115\n",
      "[38]\tvalid_0's l1: 0.496934\tvalid_0's binary_logloss: 0.687958\n",
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      "[44]\tvalid_0's l1: 0.496304\tvalid_0's binary_logloss: 0.686979\n",
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      "[46]\tvalid_0's l1: 0.496154\tvalid_0's binary_logloss: 0.686807\n",
      "[47]\tvalid_0's l1: 0.496091\tvalid_0's binary_logloss: 0.686651\n",
      "[48]\tvalid_0's l1: 0.49603\tvalid_0's binary_logloss: 0.686587\n",
      "[49]\tvalid_0's l1: 0.495877\tvalid_0's binary_logloss: 0.686339\n",
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      "[59]\tvalid_0's l1: 0.494943\tvalid_0's binary_logloss: 0.684859\n",
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      "[79]\tvalid_0's l1: 0.493337\tvalid_0's binary_logloss: 0.68276\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[80]\tvalid_0's l1: 0.493199\tvalid_0's binary_logloss: 0.682583\n",
      "[81]\tvalid_0's l1: 0.493075\tvalid_0's binary_logloss: 0.682365\n",
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      "[206]\tvalid_0's l1: 0.484592\tvalid_0's binary_logloss: 0.672722\n",
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      "[209]\tvalid_0's l1: 0.484486\tvalid_0's binary_logloss: 0.672617\n",
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      "[212]\tvalid_0's l1: 0.48425\tvalid_0's binary_logloss: 0.672365\n",
      "[213]\tvalid_0's l1: 0.48417\tvalid_0's binary_logloss: 0.672336\n",
      "[214]\tvalid_0's l1: 0.484131\tvalid_0's binary_logloss: 0.672319\n",
      "[215]\tvalid_0's l1: 0.484121\tvalid_0's binary_logloss: 0.672425\n",
      "[216]\tvalid_0's l1: 0.484075\tvalid_0's binary_logloss: 0.672388\n",
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      "[218]\tvalid_0's l1: 0.483978\tvalid_0's binary_logloss: 0.672187\n",
      "[219]\tvalid_0's l1: 0.483984\tvalid_0's binary_logloss: 0.672242\n",
      "[220]\tvalid_0's l1: 0.483975\tvalid_0's binary_logloss: 0.672351\n",
      "[221]\tvalid_0's l1: 0.483997\tvalid_0's binary_logloss: 0.672485\n",
      "[222]\tvalid_0's l1: 0.483918\tvalid_0's binary_logloss: 0.672305\n",
      "[223]\tvalid_0's l1: 0.483884\tvalid_0's binary_logloss: 0.672242\n",
      "Early stopping, best iteration is:\n",
      "[218]\tvalid_0's l1: 0.483978\tvalid_0's binary_logloss: 0.672187\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1]\tvalid_0's l1: 0.501158\tvalid_0's binary_logloss: 0.696009\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501045\tvalid_0's binary_logloss: 0.695767\n",
      "[3]\tvalid_0's l1: 0.501061\tvalid_0's binary_logloss: 0.695775\n",
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      "[5]\tvalid_0's l1: 0.500969\tvalid_0's binary_logloss: 0.695568\n",
      "[6]\tvalid_0's l1: 0.500944\tvalid_0's binary_logloss: 0.695518\n",
      "[7]\tvalid_0's l1: 0.500817\tvalid_0's binary_logloss: 0.695262\n",
      "[8]\tvalid_0's l1: 0.500853\tvalid_0's binary_logloss: 0.695341\n",
      "[9]\tvalid_0's l1: 0.500873\tvalid_0's binary_logloss: 0.695392\n",
      "[10]\tvalid_0's l1: 0.500831\tvalid_0's binary_logloss: 0.695308\n",
      "[11]\tvalid_0's l1: 0.500815\tvalid_0's binary_logloss: 0.695299\n",
      "[12]\tvalid_0's l1: 0.500851\tvalid_0's binary_logloss: 0.695388\n",
      "Early stopping, best iteration is:\n",
      "[7]\tvalid_0's l1: 0.500817\tvalid_0's binary_logloss: 0.695262\n",
      "[1]\tvalid_0's l1: 0.501155\tvalid_0's binary_logloss: 0.696003\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501022\tvalid_0's binary_logloss: 0.695718\n",
      "[3]\tvalid_0's l1: 0.50089\tvalid_0's binary_logloss: 0.695449\n",
      "[4]\tvalid_0's l1: 0.50076\tvalid_0's binary_logloss: 0.695197\n",
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      "[6]\tvalid_0's l1: 0.500502\tvalid_0's binary_logloss: 0.69474\n",
      "[7]\tvalid_0's l1: 0.500482\tvalid_0's binary_logloss: 0.694732\n",
      "[8]\tvalid_0's l1: 0.500462\tvalid_0's binary_logloss: 0.694731\n",
      "[9]\tvalid_0's l1: 0.500441\tvalid_0's binary_logloss: 0.694735\n",
      "[10]\tvalid_0's l1: 0.500422\tvalid_0's binary_logloss: 0.694744\n",
      "[11]\tvalid_0's l1: 0.500402\tvalid_0's binary_logloss: 0.69476\n",
      "[12]\tvalid_0's l1: 0.500382\tvalid_0's binary_logloss: 0.69478\n",
      "[13]\tvalid_0's l1: 0.500363\tvalid_0's binary_logloss: 0.694806\n",
      "Early stopping, best iteration is:\n",
      "[8]\tvalid_0's l1: 0.500462\tvalid_0's binary_logloss: 0.694731\n",
      "[1]\tvalid_0's l1: 0.501149\tvalid_0's binary_logloss: 0.696022\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501007\tvalid_0's binary_logloss: 0.695745\n",
      "[3]\tvalid_0's l1: 0.500871\tvalid_0's binary_logloss: 0.695495\n",
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      "[6]\tvalid_0's l1: 0.500541\tvalid_0's binary_logloss: 0.694882\n",
      "[7]\tvalid_0's l1: 0.500405\tvalid_0's binary_logloss: 0.694661\n",
      "[8]\tvalid_0's l1: 0.500311\tvalid_0's binary_logloss: 0.694513\n",
      "[9]\tvalid_0's l1: 0.500212\tvalid_0's binary_logloss: 0.69437\n",
      "[10]\tvalid_0's l1: 0.500079\tvalid_0's binary_logloss: 0.694176\n",
      "[11]\tvalid_0's l1: 0.499982\tvalid_0's binary_logloss: 0.694057\n",
      "[12]\tvalid_0's l1: 0.499884\tvalid_0's binary_logloss: 0.693953\n",
      "[13]\tvalid_0's l1: 0.49977\tvalid_0's binary_logloss: 0.693817\n",
      "[14]\tvalid_0's l1: 0.499681\tvalid_0's binary_logloss: 0.693747\n",
      "[15]\tvalid_0's l1: 0.499581\tvalid_0's binary_logloss: 0.69353\n",
      "[16]\tvalid_0's l1: 0.499468\tvalid_0's binary_logloss: 0.693425\n",
      "[17]\tvalid_0's l1: 0.499352\tvalid_0's binary_logloss: 0.693303\n",
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      "[19]\tvalid_0's l1: 0.49915\tvalid_0's binary_logloss: 0.69316\n",
      "[20]\tvalid_0's l1: 0.499135\tvalid_0's binary_logloss: 0.693231\n",
      "[21]\tvalid_0's l1: 0.499127\tvalid_0's binary_logloss: 0.693327\n",
      "[22]\tvalid_0's l1: 0.499006\tvalid_0's binary_logloss: 0.69309\n",
      "[23]\tvalid_0's l1: 0.498867\tvalid_0's binary_logloss: 0.692944\n",
      "[24]\tvalid_0's l1: 0.498829\tvalid_0's binary_logloss: 0.692995\n",
      "[25]\tvalid_0's l1: 0.498815\tvalid_0's binary_logloss: 0.693107\n",
      "[26]\tvalid_0's l1: 0.498696\tvalid_0's binary_logloss: 0.692889\n",
      "[27]\tvalid_0's l1: 0.49866\tvalid_0's binary_logloss: 0.692968\n",
      "[28]\tvalid_0's l1: 0.498565\tvalid_0's binary_logloss: 0.692925\n",
      "[29]\tvalid_0's l1: 0.498528\tvalid_0's binary_logloss: 0.693018\n",
      "[30]\tvalid_0's l1: 0.498515\tvalid_0's binary_logloss: 0.693168\n",
      "[31]\tvalid_0's l1: 0.498498\tvalid_0's binary_logloss: 0.693225\n",
      "Early stopping, best iteration is:\n",
      "[26]\tvalid_0's l1: 0.498696\tvalid_0's binary_logloss: 0.692889\n",
      "[1]\tvalid_0's l1: 0.50121\tvalid_0's binary_logloss: 0.696223\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501076\tvalid_0's binary_logloss: 0.695997\n",
      "[3]\tvalid_0's l1: 0.500942\tvalid_0's binary_logloss: 0.695784\n",
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      "[7]\tvalid_0's l1: 0.500565\tvalid_0's binary_logloss: 0.695353\n",
      "[8]\tvalid_0's l1: 0.500437\tvalid_0's binary_logloss: 0.695196\n",
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      "[10]\tvalid_0's l1: 0.500295\tvalid_0's binary_logloss: 0.695131\n",
      "[11]\tvalid_0's l1: 0.500202\tvalid_0's binary_logloss: 0.694949\n",
      "[12]\tvalid_0's l1: 0.50008\tvalid_0's binary_logloss: 0.694711\n",
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      "[14]\tvalid_0's l1: 0.499914\tvalid_0's binary_logloss: 0.694537\n",
      "[15]\tvalid_0's l1: 0.499728\tvalid_0's binary_logloss: 0.694166\n",
      "[16]\tvalid_0's l1: 0.499653\tvalid_0's binary_logloss: 0.694151\n",
      "[17]\tvalid_0's l1: 0.499498\tvalid_0's binary_logloss: 0.693874\n",
      "[18]\tvalid_0's l1: 0.499424\tvalid_0's binary_logloss: 0.693874\n",
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      "[20]\tvalid_0's l1: 0.499189\tvalid_0's binary_logloss: 0.693566\n",
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      "[41]\tvalid_0's l1: 0.496464\tvalid_0's binary_logloss: 0.69103\n",
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      "[44]\tvalid_0's l1: 0.496152\tvalid_0's binary_logloss: 0.691067\n",
      "[45]\tvalid_0's l1: 0.495992\tvalid_0's binary_logloss: 0.690933\n",
      "[46]\tvalid_0's l1: 0.495858\tvalid_0's binary_logloss: 0.690874\n",
      "[47]\tvalid_0's l1: 0.495866\tvalid_0's binary_logloss: 0.69107\n",
      "[48]\tvalid_0's l1: 0.49569\tvalid_0's binary_logloss: 0.690862\n",
      "[49]\tvalid_0's l1: 0.495563\tvalid_0's binary_logloss: 0.690777\n",
      "[50]\tvalid_0's l1: 0.495476\tvalid_0's binary_logloss: 0.690724\n",
      "[51]\tvalid_0's l1: 0.495469\tvalid_0's binary_logloss: 0.690933\n",
      "[52]\tvalid_0's l1: 0.49532\tvalid_0's binary_logloss: 0.69086\n",
      "[53]\tvalid_0's l1: 0.495172\tvalid_0's binary_logloss: 0.690745\n",
      "[54]\tvalid_0's l1: 0.495087\tvalid_0's binary_logloss: 0.690698\n",
      "[55]\tvalid_0's l1: 0.495002\tvalid_0's binary_logloss: 0.690656\n",
      "[56]\tvalid_0's l1: 0.494786\tvalid_0's binary_logloss: 0.690417\n",
      "[57]\tvalid_0's l1: 0.494702\tvalid_0's binary_logloss: 0.690381\n",
      "[58]\tvalid_0's l1: 0.494696\tvalid_0's binary_logloss: 0.690602\n",
      "[59]\tvalid_0's l1: 0.494567\tvalid_0's binary_logloss: 0.690553\n",
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      "[65]\tvalid_0's l1: 0.493985\tvalid_0's binary_logloss: 0.690192\n",
      "[66]\tvalid_0's l1: 0.493881\tvalid_0's binary_logloss: 0.690116\n",
      "[67]\tvalid_0's l1: 0.493902\tvalid_0's binary_logloss: 0.690384\n",
      "[68]\tvalid_0's l1: 0.493756\tvalid_0's binary_logloss: 0.690291\n",
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      "[70]\tvalid_0's l1: 0.493628\tvalid_0's binary_logloss: 0.690401\n",
      "[71]\tvalid_0's l1: 0.493481\tvalid_0's binary_logloss: 0.690244\n",
      "Early stopping, best iteration is:\n",
      "[66]\tvalid_0's l1: 0.493881\tvalid_0's binary_logloss: 0.690116\n",
      "[1]\tvalid_0's l1: 0.501228\tvalid_0's binary_logloss: 0.696199\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501127\tvalid_0's binary_logloss: 0.695984\n",
      "[3]\tvalid_0's l1: 0.500967\tvalid_0's binary_logloss: 0.695633\n",
      "[4]\tvalid_0's l1: 0.500868\tvalid_0's binary_logloss: 0.695427\n",
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      "[10]\tvalid_0's l1: 0.49996\tvalid_0's binary_logloss: 0.693573\n",
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      "[47]\tvalid_0's l1: 0.496091\tvalid_0's binary_logloss: 0.686651\n",
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      "[50]\tvalid_0's l1: 0.495815\tvalid_0's binary_logloss: 0.686184\n",
      "[51]\tvalid_0's l1: 0.495728\tvalid_0's binary_logloss: 0.686067\n",
      "[52]\tvalid_0's l1: 0.495576\tvalid_0's binary_logloss: 0.685827\n",
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      "[68]\tvalid_0's l1: 0.494026\tvalid_0's binary_logloss: 0.683527\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[69]\tvalid_0's l1: 0.494013\tvalid_0's binary_logloss: 0.683536\n",
      "[70]\tvalid_0's l1: 0.493902\tvalid_0's binary_logloss: 0.683431\n",
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      "[209]\tvalid_0's l1: 0.484486\tvalid_0's binary_logloss: 0.672617\n",
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      "[211]\tvalid_0's l1: 0.484404\tvalid_0's binary_logloss: 0.672637\n",
      "[212]\tvalid_0's l1: 0.48425\tvalid_0's binary_logloss: 0.672365\n",
      "[213]\tvalid_0's l1: 0.48417\tvalid_0's binary_logloss: 0.672336\n",
      "[214]\tvalid_0's l1: 0.484131\tvalid_0's binary_logloss: 0.672319\n",
      "[215]\tvalid_0's l1: 0.484121\tvalid_0's binary_logloss: 0.672425\n",
      "[216]\tvalid_0's l1: 0.484075\tvalid_0's binary_logloss: 0.672388\n",
      "[217]\tvalid_0's l1: 0.484075\tvalid_0's binary_logloss: 0.672391\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[218]\tvalid_0's l1: 0.483978\tvalid_0's binary_logloss: 0.672187\n",
      "[219]\tvalid_0's l1: 0.483984\tvalid_0's binary_logloss: 0.672242\n",
      "[220]\tvalid_0's l1: 0.483975\tvalid_0's binary_logloss: 0.672351\n",
      "[221]\tvalid_0's l1: 0.483997\tvalid_0's binary_logloss: 0.672485\n",
      "[222]\tvalid_0's l1: 0.483918\tvalid_0's binary_logloss: 0.672305\n",
      "[223]\tvalid_0's l1: 0.483884\tvalid_0's binary_logloss: 0.672242\n",
      "Early stopping, best iteration is:\n",
      "[218]\tvalid_0's l1: 0.483978\tvalid_0's binary_logloss: 0.672187\n",
      "[1]\tvalid_0's l1: 0.501158\tvalid_0's binary_logloss: 0.696009\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501045\tvalid_0's binary_logloss: 0.695767\n",
      "[3]\tvalid_0's l1: 0.501061\tvalid_0's binary_logloss: 0.695775\n",
      "[4]\tvalid_0's l1: 0.500953\tvalid_0's binary_logloss: 0.695547\n",
      "[5]\tvalid_0's l1: 0.500969\tvalid_0's binary_logloss: 0.695568\n",
      "[6]\tvalid_0's l1: 0.500944\tvalid_0's binary_logloss: 0.695518\n",
      "[7]\tvalid_0's l1: 0.500817\tvalid_0's binary_logloss: 0.695262\n",
      "[8]\tvalid_0's l1: 0.500853\tvalid_0's binary_logloss: 0.695341\n",
      "[9]\tvalid_0's l1: 0.500873\tvalid_0's binary_logloss: 0.695392\n",
      "[10]\tvalid_0's l1: 0.500831\tvalid_0's binary_logloss: 0.695308\n",
      "[11]\tvalid_0's l1: 0.500815\tvalid_0's binary_logloss: 0.695299\n",
      "[12]\tvalid_0's l1: 0.500851\tvalid_0's binary_logloss: 0.695388\n",
      "Early stopping, best iteration is:\n",
      "[7]\tvalid_0's l1: 0.500817\tvalid_0's binary_logloss: 0.695262\n",
      "[1]\tvalid_0's l1: 0.501155\tvalid_0's binary_logloss: 0.696003\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501022\tvalid_0's binary_logloss: 0.695718\n",
      "[3]\tvalid_0's l1: 0.50089\tvalid_0's binary_logloss: 0.695449\n",
      "[4]\tvalid_0's l1: 0.50076\tvalid_0's binary_logloss: 0.695197\n",
      "[5]\tvalid_0's l1: 0.50063\tvalid_0's binary_logloss: 0.694961\n",
      "[6]\tvalid_0's l1: 0.500502\tvalid_0's binary_logloss: 0.69474\n",
      "[7]\tvalid_0's l1: 0.500482\tvalid_0's binary_logloss: 0.694732\n",
      "[8]\tvalid_0's l1: 0.500462\tvalid_0's binary_logloss: 0.694731\n",
      "[9]\tvalid_0's l1: 0.500441\tvalid_0's binary_logloss: 0.694735\n",
      "[10]\tvalid_0's l1: 0.500422\tvalid_0's binary_logloss: 0.694744\n",
      "[11]\tvalid_0's l1: 0.500402\tvalid_0's binary_logloss: 0.69476\n",
      "[12]\tvalid_0's l1: 0.500382\tvalid_0's binary_logloss: 0.69478\n",
      "[13]\tvalid_0's l1: 0.500363\tvalid_0's binary_logloss: 0.694806\n",
      "Early stopping, best iteration is:\n",
      "[8]\tvalid_0's l1: 0.500462\tvalid_0's binary_logloss: 0.694731\n",
      "[1]\tvalid_0's l1: 0.501149\tvalid_0's binary_logloss: 0.696022\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501007\tvalid_0's binary_logloss: 0.695745\n",
      "[3]\tvalid_0's l1: 0.500871\tvalid_0's binary_logloss: 0.695495\n",
      "[4]\tvalid_0's l1: 0.500774\tvalid_0's binary_logloss: 0.695296\n",
      "[5]\tvalid_0's l1: 0.500636\tvalid_0's binary_logloss: 0.695055\n",
      "[6]\tvalid_0's l1: 0.500541\tvalid_0's binary_logloss: 0.694882\n",
      "[7]\tvalid_0's l1: 0.500405\tvalid_0's binary_logloss: 0.694661\n",
      "[8]\tvalid_0's l1: 0.500311\tvalid_0's binary_logloss: 0.694513\n",
      "[9]\tvalid_0's l1: 0.500212\tvalid_0's binary_logloss: 0.69437\n",
      "[10]\tvalid_0's l1: 0.500079\tvalid_0's binary_logloss: 0.694176\n",
      "[11]\tvalid_0's l1: 0.499982\tvalid_0's binary_logloss: 0.694057\n",
      "[12]\tvalid_0's l1: 0.499884\tvalid_0's binary_logloss: 0.693953\n",
      "[13]\tvalid_0's l1: 0.49977\tvalid_0's binary_logloss: 0.693817\n",
      "[14]\tvalid_0's l1: 0.499681\tvalid_0's binary_logloss: 0.693747\n",
      "[15]\tvalid_0's l1: 0.499581\tvalid_0's binary_logloss: 0.69353\n",
      "[16]\tvalid_0's l1: 0.499468\tvalid_0's binary_logloss: 0.693425\n",
      "[17]\tvalid_0's l1: 0.499352\tvalid_0's binary_logloss: 0.693303\n",
      "[18]\tvalid_0's l1: 0.499246\tvalid_0's binary_logloss: 0.693232\n",
      "[19]\tvalid_0's l1: 0.49915\tvalid_0's binary_logloss: 0.69316\n",
      "[20]\tvalid_0's l1: 0.499135\tvalid_0's binary_logloss: 0.693231\n",
      "[21]\tvalid_0's l1: 0.499127\tvalid_0's binary_logloss: 0.693327\n",
      "[22]\tvalid_0's l1: 0.499006\tvalid_0's binary_logloss: 0.69309\n",
      "[23]\tvalid_0's l1: 0.498867\tvalid_0's binary_logloss: 0.692944\n",
      "[24]\tvalid_0's l1: 0.498829\tvalid_0's binary_logloss: 0.692995\n",
      "[25]\tvalid_0's l1: 0.498815\tvalid_0's binary_logloss: 0.693107\n",
      "[26]\tvalid_0's l1: 0.498696\tvalid_0's binary_logloss: 0.692889\n",
      "[27]\tvalid_0's l1: 0.49866\tvalid_0's binary_logloss: 0.692968\n",
      "[28]\tvalid_0's l1: 0.498565\tvalid_0's binary_logloss: 0.692925\n",
      "[29]\tvalid_0's l1: 0.498528\tvalid_0's binary_logloss: 0.693018\n",
      "[30]\tvalid_0's l1: 0.498515\tvalid_0's binary_logloss: 0.693168\n",
      "[31]\tvalid_0's l1: 0.498498\tvalid_0's binary_logloss: 0.693225\n",
      "Early stopping, best iteration is:\n",
      "[26]\tvalid_0's l1: 0.498696\tvalid_0's binary_logloss: 0.692889\n",
      "[1]\tvalid_0's l1: 0.50121\tvalid_0's binary_logloss: 0.696223\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501076\tvalid_0's binary_logloss: 0.695997\n",
      "[3]\tvalid_0's l1: 0.500942\tvalid_0's binary_logloss: 0.695784\n",
      "[4]\tvalid_0's l1: 0.500828\tvalid_0's binary_logloss: 0.695627\n",
      "[5]\tvalid_0's l1: 0.500744\tvalid_0's binary_logloss: 0.695523\n",
      "[6]\tvalid_0's l1: 0.500631\tvalid_0's binary_logloss: 0.69539\n",
      "[7]\tvalid_0's l1: 0.500565\tvalid_0's binary_logloss: 0.695353\n",
      "[8]\tvalid_0's l1: 0.500437\tvalid_0's binary_logloss: 0.695196\n",
      "[9]\tvalid_0's l1: 0.500356\tvalid_0's binary_logloss: 0.69513\n",
      "[10]\tvalid_0's l1: 0.500295\tvalid_0's binary_logloss: 0.695131\n",
      "[11]\tvalid_0's l1: 0.500202\tvalid_0's binary_logloss: 0.694949\n",
      "[12]\tvalid_0's l1: 0.50008\tvalid_0's binary_logloss: 0.694711\n",
      "[13]\tvalid_0's l1: 0.500004\tvalid_0's binary_logloss: 0.694679\n",
      "[14]\tvalid_0's l1: 0.499914\tvalid_0's binary_logloss: 0.694537\n",
      "[15]\tvalid_0's l1: 0.499728\tvalid_0's binary_logloss: 0.694166\n",
      "[16]\tvalid_0's l1: 0.499653\tvalid_0's binary_logloss: 0.694151\n",
      "[17]\tvalid_0's l1: 0.499498\tvalid_0's binary_logloss: 0.693874\n",
      "[18]\tvalid_0's l1: 0.499424\tvalid_0's binary_logloss: 0.693874\n",
      "[19]\tvalid_0's l1: 0.499337\tvalid_0's binary_logloss: 0.693781\n",
      "[20]\tvalid_0's l1: 0.499189\tvalid_0's binary_logloss: 0.693566\n",
      "[21]\tvalid_0's l1: 0.499009\tvalid_0's binary_logloss: 0.693259\n",
      "[22]\tvalid_0's l1: 0.498872\tvalid_0's binary_logloss: 0.693085\n",
      "[23]\tvalid_0's l1: 0.498723\tvalid_0's binary_logloss: 0.692869\n",
      "[24]\tvalid_0's l1: 0.498667\tvalid_0's binary_logloss: 0.692942\n",
      "[25]\tvalid_0's l1: 0.498491\tvalid_0's binary_logloss: 0.692679\n",
      "[26]\tvalid_0's l1: 0.498348\tvalid_0's binary_logloss: 0.692499\n",
      "[27]\tvalid_0's l1: 0.498224\tvalid_0's binary_logloss: 0.692366\n",
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      "[31]\tvalid_0's l1: 0.497712\tvalid_0's binary_logloss: 0.691957\n",
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      "[33]\tvalid_0's l1: 0.497455\tvalid_0's binary_logloss: 0.69172\n",
      "[34]\tvalid_0's l1: 0.497349\tvalid_0's binary_logloss: 0.691647\n",
      "[35]\tvalid_0's l1: 0.497212\tvalid_0's binary_logloss: 0.69151\n",
      "[36]\tvalid_0's l1: 0.497167\tvalid_0's binary_logloss: 0.691669\n",
      "[37]\tvalid_0's l1: 0.497031\tvalid_0's binary_logloss: 0.691564\n",
      "[38]\tvalid_0's l1: 0.496825\tvalid_0's binary_logloss: 0.691305\n",
      "[39]\tvalid_0's l1: 0.496711\tvalid_0's binary_logloss: 0.691258\n",
      "[40]\tvalid_0's l1: 0.49662\tvalid_0's binary_logloss: 0.691185\n",
      "[41]\tvalid_0's l1: 0.496464\tvalid_0's binary_logloss: 0.69103\n",
      "[42]\tvalid_0's l1: 0.49642\tvalid_0's binary_logloss: 0.691212\n",
      "[43]\tvalid_0's l1: 0.496283\tvalid_0's binary_logloss: 0.691126\n",
      "[44]\tvalid_0's l1: 0.496152\tvalid_0's binary_logloss: 0.691067\n",
      "[45]\tvalid_0's l1: 0.495992\tvalid_0's binary_logloss: 0.690933\n",
      "[46]\tvalid_0's l1: 0.495858\tvalid_0's binary_logloss: 0.690874\n",
      "[47]\tvalid_0's l1: 0.495866\tvalid_0's binary_logloss: 0.69107\n",
      "[48]\tvalid_0's l1: 0.49569\tvalid_0's binary_logloss: 0.690862\n",
      "[49]\tvalid_0's l1: 0.495563\tvalid_0's binary_logloss: 0.690777\n",
      "[50]\tvalid_0's l1: 0.495476\tvalid_0's binary_logloss: 0.690724\n",
      "[51]\tvalid_0's l1: 0.495469\tvalid_0's binary_logloss: 0.690933\n",
      "[52]\tvalid_0's l1: 0.49532\tvalid_0's binary_logloss: 0.69086\n",
      "[53]\tvalid_0's l1: 0.495172\tvalid_0's binary_logloss: 0.690745\n",
      "[54]\tvalid_0's l1: 0.495087\tvalid_0's binary_logloss: 0.690698\n",
      "[55]\tvalid_0's l1: 0.495002\tvalid_0's binary_logloss: 0.690656\n",
      "[56]\tvalid_0's l1: 0.494786\tvalid_0's binary_logloss: 0.690417\n",
      "[57]\tvalid_0's l1: 0.494702\tvalid_0's binary_logloss: 0.690381\n",
      "[58]\tvalid_0's l1: 0.494696\tvalid_0's binary_logloss: 0.690602\n",
      "[59]\tvalid_0's l1: 0.494567\tvalid_0's binary_logloss: 0.690553\n",
      "[60]\tvalid_0's l1: 0.494465\tvalid_0's binary_logloss: 0.690479\n",
      "[61]\tvalid_0's l1: 0.494383\tvalid_0's binary_logloss: 0.690451\n",
      "[62]\tvalid_0's l1: 0.494247\tvalid_0's binary_logloss: 0.690308\n",
      "[63]\tvalid_0's l1: 0.494165\tvalid_0's binary_logloss: 0.690285\n",
      "[64]\tvalid_0's l1: 0.494038\tvalid_0's binary_logloss: 0.690172\n",
      "[65]\tvalid_0's l1: 0.493985\tvalid_0's binary_logloss: 0.690192\n",
      "[66]\tvalid_0's l1: 0.493881\tvalid_0's binary_logloss: 0.690116\n",
      "[67]\tvalid_0's l1: 0.493902\tvalid_0's binary_logloss: 0.690384\n",
      "[68]\tvalid_0's l1: 0.493756\tvalid_0's binary_logloss: 0.690291\n",
      "[69]\tvalid_0's l1: 0.493607\tvalid_0's binary_logloss: 0.690123\n",
      "[70]\tvalid_0's l1: 0.493628\tvalid_0's binary_logloss: 0.690401\n",
      "[71]\tvalid_0's l1: 0.493481\tvalid_0's binary_logloss: 0.690244\n",
      "Early stopping, best iteration is:\n",
      "[66]\tvalid_0's l1: 0.493881\tvalid_0's binary_logloss: 0.690116\n",
      "[1]\tvalid_0's l1: 0.501228\tvalid_0's binary_logloss: 0.696199\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501127\tvalid_0's binary_logloss: 0.695984\n",
      "[3]\tvalid_0's l1: 0.500967\tvalid_0's binary_logloss: 0.695633\n",
      "[4]\tvalid_0's l1: 0.500868\tvalid_0's binary_logloss: 0.695427\n",
      "[5]\tvalid_0's l1: 0.50071\tvalid_0's binary_logloss: 0.695087\n",
      "[6]\tvalid_0's l1: 0.500613\tvalid_0's binary_logloss: 0.69489\n",
      "[7]\tvalid_0's l1: 0.50038\tvalid_0's binary_logloss: 0.694409\n",
      "[8]\tvalid_0's l1: 0.500284\tvalid_0's binary_logloss: 0.69422\n",
      "[9]\tvalid_0's l1: 0.500054\tvalid_0's binary_logloss: 0.693754\n",
      "[10]\tvalid_0's l1: 0.49996\tvalid_0's binary_logloss: 0.693573\n",
      "[11]\tvalid_0's l1: 0.499807\tvalid_0's binary_logloss: 0.693253\n",
      "[12]\tvalid_0's l1: 0.49958\tvalid_0's binary_logloss: 0.692806\n",
      "[13]\tvalid_0's l1: 0.499488\tvalid_0's binary_logloss: 0.692615\n",
      "[14]\tvalid_0's l1: 0.499337\tvalid_0's binary_logloss: 0.692307\n",
      "[15]\tvalid_0's l1: 0.499246\tvalid_0's binary_logloss: 0.692143\n",
      "[16]\tvalid_0's l1: 0.499025\tvalid_0's binary_logloss: 0.691717\n",
      "[17]\tvalid_0's l1: 0.498936\tvalid_0's binary_logloss: 0.69156\n",
      "[18]\tvalid_0's l1: 0.498717\tvalid_0's binary_logloss: 0.691148\n",
      "[19]\tvalid_0's l1: 0.498633\tvalid_0's binary_logloss: 0.690986\n",
      "[20]\tvalid_0's l1: 0.498511\tvalid_0's binary_logloss: 0.69074\n",
      "[21]\tvalid_0's l1: 0.498425\tvalid_0's binary_logloss: 0.690594\n",
      "[22]\tvalid_0's l1: 0.498384\tvalid_0's binary_logloss: 0.690514\n",
      "[23]\tvalid_0's l1: 0.498311\tvalid_0's binary_logloss: 0.690368\n",
      "[24]\tvalid_0's l1: 0.498235\tvalid_0's binary_logloss: 0.690197\n",
      "[25]\tvalid_0's l1: 0.498183\tvalid_0's binary_logloss: 0.690102\n",
      "[26]\tvalid_0's l1: 0.498123\tvalid_0's binary_logloss: 0.689981\n",
      "[27]\tvalid_0's l1: 0.498048\tvalid_0's binary_logloss: 0.689817\n",
      "[28]\tvalid_0's l1: 0.497917\tvalid_0's binary_logloss: 0.689591\n",
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      "[30]\tvalid_0's l1: 0.497716\tvalid_0's binary_logloss: 0.689239\n",
      "[31]\tvalid_0's l1: 0.497642\tvalid_0's binary_logloss: 0.68908\n",
      "[32]\tvalid_0's l1: 0.497548\tvalid_0's binary_logloss: 0.688929\n",
      "[33]\tvalid_0's l1: 0.49742\tvalid_0's binary_logloss: 0.688723\n",
      "[34]\tvalid_0's l1: 0.497327\tvalid_0's binary_logloss: 0.688577\n",
      "[35]\tvalid_0's l1: 0.4972\tvalid_0's binary_logloss: 0.688382\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[36]\tvalid_0's l1: 0.497136\tvalid_0's binary_logloss: 0.6883\n",
      "[37]\tvalid_0's l1: 0.49701\tvalid_0's binary_logloss: 0.688115\n",
      "[38]\tvalid_0's l1: 0.496934\tvalid_0's binary_logloss: 0.687958\n",
      "[39]\tvalid_0's l1: 0.496844\tvalid_0's binary_logloss: 0.687821\n",
      "[40]\tvalid_0's l1: 0.496736\tvalid_0's binary_logloss: 0.687617\n",
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      "[42]\tvalid_0's l1: 0.496549\tvalid_0's binary_logloss: 0.687369\n",
      "[43]\tvalid_0's l1: 0.496393\tvalid_0's binary_logloss: 0.687107\n",
      "[44]\tvalid_0's l1: 0.496304\tvalid_0's binary_logloss: 0.686979\n",
      "[45]\tvalid_0's l1: 0.496275\tvalid_0's binary_logloss: 0.686964\n",
      "[46]\tvalid_0's l1: 0.496154\tvalid_0's binary_logloss: 0.686807\n",
      "[47]\tvalid_0's l1: 0.496091\tvalid_0's binary_logloss: 0.686651\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[173]\tvalid_0's l1: 0.486505\tvalid_0's binary_logloss: 0.674612\n",
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      "[216]\tvalid_0's l1: 0.484075\tvalid_0's binary_logloss: 0.672388\n",
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      "[218]\tvalid_0's l1: 0.483978\tvalid_0's binary_logloss: 0.672187\n",
      "[219]\tvalid_0's l1: 0.483984\tvalid_0's binary_logloss: 0.672242\n",
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      "[223]\tvalid_0's l1: 0.483884\tvalid_0's binary_logloss: 0.672242\n",
      "Early stopping, best iteration is:\n",
      "[218]\tvalid_0's l1: 0.483978\tvalid_0's binary_logloss: 0.672187\n",
      "[1]\tvalid_0's l1: 0.501158\tvalid_0's binary_logloss: 0.696009\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501045\tvalid_0's binary_logloss: 0.695767\n",
      "[3]\tvalid_0's l1: 0.501061\tvalid_0's binary_logloss: 0.695775\n",
      "[4]\tvalid_0's l1: 0.500953\tvalid_0's binary_logloss: 0.695547\n",
      "[5]\tvalid_0's l1: 0.500969\tvalid_0's binary_logloss: 0.695568\n",
      "[6]\tvalid_0's l1: 0.500944\tvalid_0's binary_logloss: 0.695518\n",
      "[7]\tvalid_0's l1: 0.500817\tvalid_0's binary_logloss: 0.695262\n",
      "[8]\tvalid_0's l1: 0.500853\tvalid_0's binary_logloss: 0.695341\n",
      "[9]\tvalid_0's l1: 0.500873\tvalid_0's binary_logloss: 0.695392\n",
      "[10]\tvalid_0's l1: 0.500831\tvalid_0's binary_logloss: 0.695308\n",
      "[11]\tvalid_0's l1: 0.500815\tvalid_0's binary_logloss: 0.695299\n",
      "[12]\tvalid_0's l1: 0.500851\tvalid_0's binary_logloss: 0.695388\n",
      "Early stopping, best iteration is:\n",
      "[7]\tvalid_0's l1: 0.500817\tvalid_0's binary_logloss: 0.695262\n",
      "[1]\tvalid_0's l1: 0.501155\tvalid_0's binary_logloss: 0.696003\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501022\tvalid_0's binary_logloss: 0.695718\n",
      "[3]\tvalid_0's l1: 0.50089\tvalid_0's binary_logloss: 0.695449\n",
      "[4]\tvalid_0's l1: 0.50076\tvalid_0's binary_logloss: 0.695197\n",
      "[5]\tvalid_0's l1: 0.50063\tvalid_0's binary_logloss: 0.694961\n",
      "[6]\tvalid_0's l1: 0.500502\tvalid_0's binary_logloss: 0.69474\n",
      "[7]\tvalid_0's l1: 0.500482\tvalid_0's binary_logloss: 0.694732\n",
      "[8]\tvalid_0's l1: 0.500462\tvalid_0's binary_logloss: 0.694731\n",
      "[9]\tvalid_0's l1: 0.500441\tvalid_0's binary_logloss: 0.694735\n",
      "[10]\tvalid_0's l1: 0.500422\tvalid_0's binary_logloss: 0.694744\n",
      "[11]\tvalid_0's l1: 0.500402\tvalid_0's binary_logloss: 0.69476\n",
      "[12]\tvalid_0's l1: 0.500382\tvalid_0's binary_logloss: 0.69478\n",
      "[13]\tvalid_0's l1: 0.500363\tvalid_0's binary_logloss: 0.694806\n",
      "Early stopping, best iteration is:\n",
      "[8]\tvalid_0's l1: 0.500462\tvalid_0's binary_logloss: 0.694731\n",
      "[1]\tvalid_0's l1: 0.501149\tvalid_0's binary_logloss: 0.696022\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501007\tvalid_0's binary_logloss: 0.695745\n",
      "[3]\tvalid_0's l1: 0.500871\tvalid_0's binary_logloss: 0.695495\n",
      "[4]\tvalid_0's l1: 0.500774\tvalid_0's binary_logloss: 0.695296\n",
      "[5]\tvalid_0's l1: 0.500636\tvalid_0's binary_logloss: 0.695055\n",
      "[6]\tvalid_0's l1: 0.500541\tvalid_0's binary_logloss: 0.694882\n",
      "[7]\tvalid_0's l1: 0.500405\tvalid_0's binary_logloss: 0.694661\n",
      "[8]\tvalid_0's l1: 0.500311\tvalid_0's binary_logloss: 0.694513\n",
      "[9]\tvalid_0's l1: 0.500212\tvalid_0's binary_logloss: 0.69437\n",
      "[10]\tvalid_0's l1: 0.500079\tvalid_0's binary_logloss: 0.694176\n",
      "[11]\tvalid_0's l1: 0.499982\tvalid_0's binary_logloss: 0.694057\n",
      "[12]\tvalid_0's l1: 0.499884\tvalid_0's binary_logloss: 0.693953\n",
      "[13]\tvalid_0's l1: 0.49977\tvalid_0's binary_logloss: 0.693817\n",
      "[14]\tvalid_0's l1: 0.499681\tvalid_0's binary_logloss: 0.693747\n",
      "[15]\tvalid_0's l1: 0.499581\tvalid_0's binary_logloss: 0.69353\n",
      "[16]\tvalid_0's l1: 0.499468\tvalid_0's binary_logloss: 0.693425\n",
      "[17]\tvalid_0's l1: 0.499352\tvalid_0's binary_logloss: 0.693303\n",
      "[18]\tvalid_0's l1: 0.499246\tvalid_0's binary_logloss: 0.693232\n",
      "[19]\tvalid_0's l1: 0.49915\tvalid_0's binary_logloss: 0.69316\n",
      "[20]\tvalid_0's l1: 0.499135\tvalid_0's binary_logloss: 0.693231\n",
      "[21]\tvalid_0's l1: 0.499127\tvalid_0's binary_logloss: 0.693327\n",
      "[22]\tvalid_0's l1: 0.499006\tvalid_0's binary_logloss: 0.69309\n",
      "[23]\tvalid_0's l1: 0.498867\tvalid_0's binary_logloss: 0.692944\n",
      "[24]\tvalid_0's l1: 0.498829\tvalid_0's binary_logloss: 0.692995\n",
      "[25]\tvalid_0's l1: 0.498815\tvalid_0's binary_logloss: 0.693107\n",
      "[26]\tvalid_0's l1: 0.498696\tvalid_0's binary_logloss: 0.692889\n",
      "[27]\tvalid_0's l1: 0.49866\tvalid_0's binary_logloss: 0.692968\n",
      "[28]\tvalid_0's l1: 0.498565\tvalid_0's binary_logloss: 0.692925\n",
      "[29]\tvalid_0's l1: 0.498528\tvalid_0's binary_logloss: 0.693018\n",
      "[30]\tvalid_0's l1: 0.498515\tvalid_0's binary_logloss: 0.693168\n",
      "[31]\tvalid_0's l1: 0.498498\tvalid_0's binary_logloss: 0.693225\n",
      "Early stopping, best iteration is:\n",
      "[26]\tvalid_0's l1: 0.498696\tvalid_0's binary_logloss: 0.692889\n",
      "[1]\tvalid_0's l1: 0.50121\tvalid_0's binary_logloss: 0.696223\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501076\tvalid_0's binary_logloss: 0.695997\n",
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      "[57]\tvalid_0's l1: 0.494702\tvalid_0's binary_logloss: 0.690381\n",
      "[58]\tvalid_0's l1: 0.494696\tvalid_0's binary_logloss: 0.690602\n",
      "[59]\tvalid_0's l1: 0.494567\tvalid_0's binary_logloss: 0.690553\n",
      "[60]\tvalid_0's l1: 0.494465\tvalid_0's binary_logloss: 0.690479\n",
      "[61]\tvalid_0's l1: 0.494383\tvalid_0's binary_logloss: 0.690451\n",
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      "[67]\tvalid_0's l1: 0.493902\tvalid_0's binary_logloss: 0.690384\n",
      "[68]\tvalid_0's l1: 0.493756\tvalid_0's binary_logloss: 0.690291\n",
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      "[70]\tvalid_0's l1: 0.493628\tvalid_0's binary_logloss: 0.690401\n",
      "[71]\tvalid_0's l1: 0.493481\tvalid_0's binary_logloss: 0.690244\n",
      "Early stopping, best iteration is:\n",
      "[66]\tvalid_0's l1: 0.493881\tvalid_0's binary_logloss: 0.690116\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1]\tvalid_0's l1: 0.501228\tvalid_0's binary_logloss: 0.696199\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501127\tvalid_0's binary_logloss: 0.695984\n",
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     ]
    },
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     "text": [
      "[140]\tvalid_0's l1: 0.488784\tvalid_0's binary_logloss: 0.677354\n",
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      "[200]\tvalid_0's l1: 0.485078\tvalid_0's binary_logloss: 0.673324\n",
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      "[202]\tvalid_0's l1: 0.484962\tvalid_0's binary_logloss: 0.673225\n",
      "[203]\tvalid_0's l1: 0.484923\tvalid_0's binary_logloss: 0.673226\n",
      "[204]\tvalid_0's l1: 0.484757\tvalid_0's binary_logloss: 0.672928\n",
      "[205]\tvalid_0's l1: 0.484641\tvalid_0's binary_logloss: 0.672731\n",
      "[206]\tvalid_0's l1: 0.484592\tvalid_0's binary_logloss: 0.672722\n",
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      "[208]\tvalid_0's l1: 0.48458\tvalid_0's binary_logloss: 0.67276\n",
      "[209]\tvalid_0's l1: 0.484486\tvalid_0's binary_logloss: 0.672617\n",
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      "[211]\tvalid_0's l1: 0.484404\tvalid_0's binary_logloss: 0.672637\n",
      "[212]\tvalid_0's l1: 0.48425\tvalid_0's binary_logloss: 0.672365\n",
      "[213]\tvalid_0's l1: 0.48417\tvalid_0's binary_logloss: 0.672336\n",
      "[214]\tvalid_0's l1: 0.484131\tvalid_0's binary_logloss: 0.672319\n",
      "[215]\tvalid_0's l1: 0.484121\tvalid_0's binary_logloss: 0.672425\n",
      "[216]\tvalid_0's l1: 0.484075\tvalid_0's binary_logloss: 0.672388\n",
      "[217]\tvalid_0's l1: 0.484075\tvalid_0's binary_logloss: 0.672391\n",
      "[218]\tvalid_0's l1: 0.483978\tvalid_0's binary_logloss: 0.672187\n",
      "[219]\tvalid_0's l1: 0.483984\tvalid_0's binary_logloss: 0.672242\n",
      "[220]\tvalid_0's l1: 0.483975\tvalid_0's binary_logloss: 0.672351\n",
      "[221]\tvalid_0's l1: 0.483997\tvalid_0's binary_logloss: 0.672485\n",
      "[222]\tvalid_0's l1: 0.483918\tvalid_0's binary_logloss: 0.672305\n",
      "[223]\tvalid_0's l1: 0.483884\tvalid_0's binary_logloss: 0.672242\n",
      "Early stopping, best iteration is:\n",
      "[218]\tvalid_0's l1: 0.483978\tvalid_0's binary_logloss: 0.672187\n",
      "[1]\tvalid_0's l1: 0.501158\tvalid_0's binary_logloss: 0.696009\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501045\tvalid_0's binary_logloss: 0.695767\n",
      "[3]\tvalid_0's l1: 0.501061\tvalid_0's binary_logloss: 0.695775\n",
      "[4]\tvalid_0's l1: 0.500953\tvalid_0's binary_logloss: 0.695547\n",
      "[5]\tvalid_0's l1: 0.500969\tvalid_0's binary_logloss: 0.695568\n",
      "[6]\tvalid_0's l1: 0.500944\tvalid_0's binary_logloss: 0.695518\n",
      "[7]\tvalid_0's l1: 0.500817\tvalid_0's binary_logloss: 0.695262\n",
      "[8]\tvalid_0's l1: 0.500853\tvalid_0's binary_logloss: 0.695341\n",
      "[9]\tvalid_0's l1: 0.500873\tvalid_0's binary_logloss: 0.695392\n",
      "[10]\tvalid_0's l1: 0.500831\tvalid_0's binary_logloss: 0.695308\n",
      "[11]\tvalid_0's l1: 0.500815\tvalid_0's binary_logloss: 0.695299\n",
      "[12]\tvalid_0's l1: 0.500851\tvalid_0's binary_logloss: 0.695388\n",
      "Early stopping, best iteration is:\n",
      "[7]\tvalid_0's l1: 0.500817\tvalid_0's binary_logloss: 0.695262\n",
      "[1]\tvalid_0's l1: 0.501155\tvalid_0's binary_logloss: 0.696003\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501022\tvalid_0's binary_logloss: 0.695718\n",
      "[3]\tvalid_0's l1: 0.50089\tvalid_0's binary_logloss: 0.695449\n",
      "[4]\tvalid_0's l1: 0.50076\tvalid_0's binary_logloss: 0.695197\n",
      "[5]\tvalid_0's l1: 0.50063\tvalid_0's binary_logloss: 0.694961\n",
      "[6]\tvalid_0's l1: 0.500502\tvalid_0's binary_logloss: 0.69474\n",
      "[7]\tvalid_0's l1: 0.500482\tvalid_0's binary_logloss: 0.694732\n",
      "[8]\tvalid_0's l1: 0.500462\tvalid_0's binary_logloss: 0.694731\n",
      "[9]\tvalid_0's l1: 0.500441\tvalid_0's binary_logloss: 0.694735\n",
      "[10]\tvalid_0's l1: 0.500422\tvalid_0's binary_logloss: 0.694744\n",
      "[11]\tvalid_0's l1: 0.500402\tvalid_0's binary_logloss: 0.69476\n",
      "[12]\tvalid_0's l1: 0.500382\tvalid_0's binary_logloss: 0.69478\n",
      "[13]\tvalid_0's l1: 0.500363\tvalid_0's binary_logloss: 0.694806\n",
      "Early stopping, best iteration is:\n",
      "[8]\tvalid_0's l1: 0.500462\tvalid_0's binary_logloss: 0.694731\n",
      "[1]\tvalid_0's l1: 0.501149\tvalid_0's binary_logloss: 0.696022\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501007\tvalid_0's binary_logloss: 0.695745\n",
      "[3]\tvalid_0's l1: 0.500871\tvalid_0's binary_logloss: 0.695495\n",
      "[4]\tvalid_0's l1: 0.500774\tvalid_0's binary_logloss: 0.695296\n",
      "[5]\tvalid_0's l1: 0.500636\tvalid_0's binary_logloss: 0.695055\n",
      "[6]\tvalid_0's l1: 0.500541\tvalid_0's binary_logloss: 0.694882\n",
      "[7]\tvalid_0's l1: 0.500405\tvalid_0's binary_logloss: 0.694661\n",
      "[8]\tvalid_0's l1: 0.500311\tvalid_0's binary_logloss: 0.694513\n",
      "[9]\tvalid_0's l1: 0.500212\tvalid_0's binary_logloss: 0.69437\n",
      "[10]\tvalid_0's l1: 0.500079\tvalid_0's binary_logloss: 0.694176\n",
      "[11]\tvalid_0's l1: 0.499982\tvalid_0's binary_logloss: 0.694057\n",
      "[12]\tvalid_0's l1: 0.499884\tvalid_0's binary_logloss: 0.693953\n",
      "[13]\tvalid_0's l1: 0.49977\tvalid_0's binary_logloss: 0.693817\n",
      "[14]\tvalid_0's l1: 0.499681\tvalid_0's binary_logloss: 0.693747\n",
      "[15]\tvalid_0's l1: 0.499581\tvalid_0's binary_logloss: 0.69353\n",
      "[16]\tvalid_0's l1: 0.499468\tvalid_0's binary_logloss: 0.693425\n",
      "[17]\tvalid_0's l1: 0.499352\tvalid_0's binary_logloss: 0.693303\n",
      "[18]\tvalid_0's l1: 0.499246\tvalid_0's binary_logloss: 0.693232\n",
      "[19]\tvalid_0's l1: 0.49915\tvalid_0's binary_logloss: 0.69316\n",
      "[20]\tvalid_0's l1: 0.499135\tvalid_0's binary_logloss: 0.693231\n",
      "[21]\tvalid_0's l1: 0.499127\tvalid_0's binary_logloss: 0.693327\n",
      "[22]\tvalid_0's l1: 0.499006\tvalid_0's binary_logloss: 0.69309\n",
      "[23]\tvalid_0's l1: 0.498867\tvalid_0's binary_logloss: 0.692944\n",
      "[24]\tvalid_0's l1: 0.498829\tvalid_0's binary_logloss: 0.692995\n",
      "[25]\tvalid_0's l1: 0.498815\tvalid_0's binary_logloss: 0.693107\n",
      "[26]\tvalid_0's l1: 0.498696\tvalid_0's binary_logloss: 0.692889\n",
      "[27]\tvalid_0's l1: 0.49866\tvalid_0's binary_logloss: 0.692968\n",
      "[28]\tvalid_0's l1: 0.498565\tvalid_0's binary_logloss: 0.692925\n",
      "[29]\tvalid_0's l1: 0.498528\tvalid_0's binary_logloss: 0.693018\n",
      "[30]\tvalid_0's l1: 0.498515\tvalid_0's binary_logloss: 0.693168\n",
      "[31]\tvalid_0's l1: 0.498498\tvalid_0's binary_logloss: 0.693225\n",
      "Early stopping, best iteration is:\n",
      "[26]\tvalid_0's l1: 0.498696\tvalid_0's binary_logloss: 0.692889\n",
      "[1]\tvalid_0's l1: 0.50121\tvalid_0's binary_logloss: 0.696223\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501076\tvalid_0's binary_logloss: 0.695997\n",
      "[3]\tvalid_0's l1: 0.500942\tvalid_0's binary_logloss: 0.695784\n",
      "[4]\tvalid_0's l1: 0.500828\tvalid_0's binary_logloss: 0.695627\n",
      "[5]\tvalid_0's l1: 0.500744\tvalid_0's binary_logloss: 0.695523\n",
      "[6]\tvalid_0's l1: 0.500631\tvalid_0's binary_logloss: 0.69539\n",
      "[7]\tvalid_0's l1: 0.500565\tvalid_0's binary_logloss: 0.695353\n",
      "[8]\tvalid_0's l1: 0.500437\tvalid_0's binary_logloss: 0.695196\n",
      "[9]\tvalid_0's l1: 0.500356\tvalid_0's binary_logloss: 0.69513\n",
      "[10]\tvalid_0's l1: 0.500295\tvalid_0's binary_logloss: 0.695131\n",
      "[11]\tvalid_0's l1: 0.500202\tvalid_0's binary_logloss: 0.694949\n",
      "[12]\tvalid_0's l1: 0.50008\tvalid_0's binary_logloss: 0.694711\n",
      "[13]\tvalid_0's l1: 0.500004\tvalid_0's binary_logloss: 0.694679\n",
      "[14]\tvalid_0's l1: 0.499914\tvalid_0's binary_logloss: 0.694537\n",
      "[15]\tvalid_0's l1: 0.499728\tvalid_0's binary_logloss: 0.694166\n",
      "[16]\tvalid_0's l1: 0.499653\tvalid_0's binary_logloss: 0.694151\n",
      "[17]\tvalid_0's l1: 0.499498\tvalid_0's binary_logloss: 0.693874\n",
      "[18]\tvalid_0's l1: 0.499424\tvalid_0's binary_logloss: 0.693874\n",
      "[19]\tvalid_0's l1: 0.499337\tvalid_0's binary_logloss: 0.693781\n",
      "[20]\tvalid_0's l1: 0.499189\tvalid_0's binary_logloss: 0.693566\n",
      "[21]\tvalid_0's l1: 0.499009\tvalid_0's binary_logloss: 0.693259\n",
      "[22]\tvalid_0's l1: 0.498872\tvalid_0's binary_logloss: 0.693085\n",
      "[23]\tvalid_0's l1: 0.498723\tvalid_0's binary_logloss: 0.692869\n",
      "[24]\tvalid_0's l1: 0.498667\tvalid_0's binary_logloss: 0.692942\n",
      "[25]\tvalid_0's l1: 0.498491\tvalid_0's binary_logloss: 0.692679\n",
      "[26]\tvalid_0's l1: 0.498348\tvalid_0's binary_logloss: 0.692499\n",
      "[27]\tvalid_0's l1: 0.498224\tvalid_0's binary_logloss: 0.692366\n",
      "[28]\tvalid_0's l1: 0.49801\tvalid_0's binary_logloss: 0.692059\n",
      "[29]\tvalid_0's l1: 0.497867\tvalid_0's binary_logloss: 0.691898\n",
      "[30]\tvalid_0's l1: 0.49782\tvalid_0's binary_logloss: 0.69203\n",
      "[31]\tvalid_0's l1: 0.497712\tvalid_0's binary_logloss: 0.691957\n",
      "[32]\tvalid_0's l1: 0.497574\tvalid_0's binary_logloss: 0.691807\n",
      "[33]\tvalid_0's l1: 0.497455\tvalid_0's binary_logloss: 0.69172\n",
      "[34]\tvalid_0's l1: 0.497349\tvalid_0's binary_logloss: 0.691647\n",
      "[35]\tvalid_0's l1: 0.497212\tvalid_0's binary_logloss: 0.69151\n",
      "[36]\tvalid_0's l1: 0.497167\tvalid_0's binary_logloss: 0.691669\n",
      "[37]\tvalid_0's l1: 0.497031\tvalid_0's binary_logloss: 0.691564\n",
      "[38]\tvalid_0's l1: 0.496825\tvalid_0's binary_logloss: 0.691305\n",
      "[39]\tvalid_0's l1: 0.496711\tvalid_0's binary_logloss: 0.691258\n",
      "[40]\tvalid_0's l1: 0.49662\tvalid_0's binary_logloss: 0.691185\n",
      "[41]\tvalid_0's l1: 0.496464\tvalid_0's binary_logloss: 0.69103\n",
      "[42]\tvalid_0's l1: 0.49642\tvalid_0's binary_logloss: 0.691212\n",
      "[43]\tvalid_0's l1: 0.496283\tvalid_0's binary_logloss: 0.691126\n",
      "[44]\tvalid_0's l1: 0.496152\tvalid_0's binary_logloss: 0.691067\n",
      "[45]\tvalid_0's l1: 0.495992\tvalid_0's binary_logloss: 0.690933\n",
      "[46]\tvalid_0's l1: 0.495858\tvalid_0's binary_logloss: 0.690874\n",
      "[47]\tvalid_0's l1: 0.495866\tvalid_0's binary_logloss: 0.69107\n",
      "[48]\tvalid_0's l1: 0.49569\tvalid_0's binary_logloss: 0.690862\n",
      "[49]\tvalid_0's l1: 0.495563\tvalid_0's binary_logloss: 0.690777\n",
      "[50]\tvalid_0's l1: 0.495476\tvalid_0's binary_logloss: 0.690724\n",
      "[51]\tvalid_0's l1: 0.495469\tvalid_0's binary_logloss: 0.690933\n",
      "[52]\tvalid_0's l1: 0.49532\tvalid_0's binary_logloss: 0.69086\n",
      "[53]\tvalid_0's l1: 0.495172\tvalid_0's binary_logloss: 0.690745\n",
      "[54]\tvalid_0's l1: 0.495087\tvalid_0's binary_logloss: 0.690698\n",
      "[55]\tvalid_0's l1: 0.495002\tvalid_0's binary_logloss: 0.690656\n",
      "[56]\tvalid_0's l1: 0.494786\tvalid_0's binary_logloss: 0.690417\n",
      "[57]\tvalid_0's l1: 0.494702\tvalid_0's binary_logloss: 0.690381\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[58]\tvalid_0's l1: 0.494696\tvalid_0's binary_logloss: 0.690602\n",
      "[59]\tvalid_0's l1: 0.494567\tvalid_0's binary_logloss: 0.690553\n",
      "[60]\tvalid_0's l1: 0.494465\tvalid_0's binary_logloss: 0.690479\n",
      "[61]\tvalid_0's l1: 0.494383\tvalid_0's binary_logloss: 0.690451\n",
      "[62]\tvalid_0's l1: 0.494247\tvalid_0's binary_logloss: 0.690308\n",
      "[63]\tvalid_0's l1: 0.494165\tvalid_0's binary_logloss: 0.690285\n",
      "[64]\tvalid_0's l1: 0.494038\tvalid_0's binary_logloss: 0.690172\n",
      "[65]\tvalid_0's l1: 0.493985\tvalid_0's binary_logloss: 0.690192\n",
      "[66]\tvalid_0's l1: 0.493881\tvalid_0's binary_logloss: 0.690116\n",
      "[67]\tvalid_0's l1: 0.493902\tvalid_0's binary_logloss: 0.690384\n",
      "[68]\tvalid_0's l1: 0.493756\tvalid_0's binary_logloss: 0.690291\n",
      "[69]\tvalid_0's l1: 0.493607\tvalid_0's binary_logloss: 0.690123\n",
      "[70]\tvalid_0's l1: 0.493628\tvalid_0's binary_logloss: 0.690401\n",
      "[71]\tvalid_0's l1: 0.493481\tvalid_0's binary_logloss: 0.690244\n",
      "Early stopping, best iteration is:\n",
      "[66]\tvalid_0's l1: 0.493881\tvalid_0's binary_logloss: 0.690116\n",
      "[1]\tvalid_0's l1: 0.501228\tvalid_0's binary_logloss: 0.696199\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501127\tvalid_0's binary_logloss: 0.695984\n",
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      "[222]\tvalid_0's l1: 0.483918\tvalid_0's binary_logloss: 0.672305\n",
      "[223]\tvalid_0's l1: 0.483884\tvalid_0's binary_logloss: 0.672242\n",
      "Early stopping, best iteration is:\n",
      "[218]\tvalid_0's l1: 0.483978\tvalid_0's binary_logloss: 0.672187\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1]\tvalid_0's l1: 0.501158\tvalid_0's binary_logloss: 0.696009\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501045\tvalid_0's binary_logloss: 0.695767\n",
      "[3]\tvalid_0's l1: 0.501061\tvalid_0's binary_logloss: 0.695775\n",
      "[4]\tvalid_0's l1: 0.500953\tvalid_0's binary_logloss: 0.695547\n",
      "[5]\tvalid_0's l1: 0.500969\tvalid_0's binary_logloss: 0.695568\n",
      "[6]\tvalid_0's l1: 0.500944\tvalid_0's binary_logloss: 0.695518\n",
      "[7]\tvalid_0's l1: 0.500817\tvalid_0's binary_logloss: 0.695262\n",
      "[8]\tvalid_0's l1: 0.500853\tvalid_0's binary_logloss: 0.695341\n",
      "[9]\tvalid_0's l1: 0.500873\tvalid_0's binary_logloss: 0.695392\n",
      "[10]\tvalid_0's l1: 0.500831\tvalid_0's binary_logloss: 0.695308\n",
      "[11]\tvalid_0's l1: 0.500815\tvalid_0's binary_logloss: 0.695299\n",
      "[12]\tvalid_0's l1: 0.500851\tvalid_0's binary_logloss: 0.695388\n",
      "Early stopping, best iteration is:\n",
      "[7]\tvalid_0's l1: 0.500817\tvalid_0's binary_logloss: 0.695262\n",
      "[1]\tvalid_0's l1: 0.501155\tvalid_0's binary_logloss: 0.696003\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501022\tvalid_0's binary_logloss: 0.695718\n",
      "[3]\tvalid_0's l1: 0.50089\tvalid_0's binary_logloss: 0.695449\n",
      "[4]\tvalid_0's l1: 0.50076\tvalid_0's binary_logloss: 0.695197\n",
      "[5]\tvalid_0's l1: 0.50063\tvalid_0's binary_logloss: 0.694961\n",
      "[6]\tvalid_0's l1: 0.500502\tvalid_0's binary_logloss: 0.69474\n",
      "[7]\tvalid_0's l1: 0.500482\tvalid_0's binary_logloss: 0.694732\n",
      "[8]\tvalid_0's l1: 0.500462\tvalid_0's binary_logloss: 0.694731\n",
      "[9]\tvalid_0's l1: 0.500441\tvalid_0's binary_logloss: 0.694735\n",
      "[10]\tvalid_0's l1: 0.500422\tvalid_0's binary_logloss: 0.694744\n",
      "[11]\tvalid_0's l1: 0.500402\tvalid_0's binary_logloss: 0.69476\n",
      "[12]\tvalid_0's l1: 0.500382\tvalid_0's binary_logloss: 0.69478\n",
      "[13]\tvalid_0's l1: 0.500363\tvalid_0's binary_logloss: 0.694806\n",
      "Early stopping, best iteration is:\n",
      "[8]\tvalid_0's l1: 0.500462\tvalid_0's binary_logloss: 0.694731\n",
      "[1]\tvalid_0's l1: 0.501151\tvalid_0's binary_logloss: 0.695996\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501011\tvalid_0's binary_logloss: 0.695693\n",
      "[3]\tvalid_0's l1: 0.500896\tvalid_0's binary_logloss: 0.695471\n",
      "[4]\tvalid_0's l1: 0.500764\tvalid_0's binary_logloss: 0.695216\n",
      "[5]\tvalid_0's l1: 0.500666\tvalid_0's binary_logloss: 0.695011\n",
      "[6]\tvalid_0's l1: 0.500574\tvalid_0's binary_logloss: 0.694842\n",
      "[7]\tvalid_0's l1: 0.500439\tvalid_0's binary_logloss: 0.694615\n",
      "[8]\tvalid_0's l1: 0.500349\tvalid_0's binary_logloss: 0.69448\n",
      "[9]\tvalid_0's l1: 0.500216\tvalid_0's binary_logloss: 0.694282\n",
      "[10]\tvalid_0's l1: 0.500128\tvalid_0's binary_logloss: 0.694178\n",
      "[11]\tvalid_0's l1: 0.499997\tvalid_0's binary_logloss: 0.694003\n",
      "[12]\tvalid_0's l1: 0.499743\tvalid_0's binary_logloss: 0.693574\n",
      "[13]\tvalid_0's l1: 0.499709\tvalid_0's binary_logloss: 0.693613\n",
      "[14]\tvalid_0's l1: 0.499633\tvalid_0's binary_logloss: 0.693562\n",
      "[15]\tvalid_0's l1: 0.499333\tvalid_0's binary_logloss: 0.693069\n",
      "[16]\tvalid_0's l1: 0.499208\tvalid_0's binary_logloss: 0.692945\n",
      "[17]\tvalid_0's l1: 0.49894\tvalid_0's binary_logloss: 0.692533\n",
      "[18]\tvalid_0's l1: 0.49882\tvalid_0's binary_logloss: 0.692449\n",
      "[19]\tvalid_0's l1: 0.498762\tvalid_0's binary_logloss: 0.692352\n",
      "[20]\tvalid_0's l1: 0.498711\tvalid_0's binary_logloss: 0.692386\n",
      "[21]\tvalid_0's l1: 0.498511\tvalid_0's binary_logloss: 0.692153\n",
      "[22]\tvalid_0's l1: 0.498434\tvalid_0's binary_logloss: 0.692038\n",
      "[23]\tvalid_0's l1: 0.498177\tvalid_0's binary_logloss: 0.691715\n",
      "[24]\tvalid_0's l1: 0.49812\tvalid_0's binary_logloss: 0.691655\n",
      "[25]\tvalid_0's l1: 0.498046\tvalid_0's binary_logloss: 0.691571\n",
      "[26]\tvalid_0's l1: 0.497846\tvalid_0's binary_logloss: 0.691384\n",
      "[27]\tvalid_0's l1: 0.497775\tvalid_0's binary_logloss: 0.691314\n",
      "[28]\tvalid_0's l1: 0.497474\tvalid_0's binary_logloss: 0.69092\n",
      "[29]\tvalid_0's l1: 0.497386\tvalid_0's binary_logloss: 0.690832\n",
      "[30]\tvalid_0's l1: 0.497191\tvalid_0's binary_logloss: 0.690685\n",
      "[31]\tvalid_0's l1: 0.497005\tvalid_0's binary_logloss: 0.690439\n",
      "[32]\tvalid_0's l1: 0.496917\tvalid_0's binary_logloss: 0.690368\n",
      "[33]\tvalid_0's l1: 0.496802\tvalid_0's binary_logloss: 0.690372\n",
      "[34]\tvalid_0's l1: 0.496623\tvalid_0's binary_logloss: 0.690177\n",
      "[35]\tvalid_0's l1: 0.496428\tvalid_0's binary_logloss: 0.690062\n",
      "[36]\tvalid_0's l1: 0.496326\tvalid_0's binary_logloss: 0.689969\n",
      "[37]\tvalid_0's l1: 0.496215\tvalid_0's binary_logloss: 0.689999\n",
      "[38]\tvalid_0's l1: 0.496157\tvalid_0's binary_logloss: 0.690096\n",
      "[39]\tvalid_0's l1: 0.496077\tvalid_0's binary_logloss: 0.690131\n",
      "[40]\tvalid_0's l1: 0.495973\tvalid_0's binary_logloss: 0.690172\n",
      "[41]\tvalid_0's l1: 0.495873\tvalid_0's binary_logloss: 0.690099\n",
      "Early stopping, best iteration is:\n",
      "[36]\tvalid_0's l1: 0.496326\tvalid_0's binary_logloss: 0.689969\n",
      "[1]\tvalid_0's l1: 0.501038\tvalid_0's binary_logloss: 0.695867\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500707\tvalid_0's binary_logloss: 0.695249\n",
      "[3]\tvalid_0's l1: 0.50038\tvalid_0's binary_logloss: 0.694654\n",
      "[4]\tvalid_0's l1: 0.500074\tvalid_0's binary_logloss: 0.694127\n",
      "[5]\tvalid_0's l1: 0.499753\tvalid_0's binary_logloss: 0.693579\n",
      "[6]\tvalid_0's l1: 0.49947\tvalid_0's binary_logloss: 0.693134\n",
      "[7]\tvalid_0's l1: 0.499172\tvalid_0's binary_logloss: 0.692678\n",
      "[8]\tvalid_0's l1: 0.498909\tvalid_0's binary_logloss: 0.692287\n",
      "[9]\tvalid_0's l1: 0.498618\tvalid_0's binary_logloss: 0.691857\n",
      "[10]\tvalid_0's l1: 0.498334\tvalid_0's binary_logloss: 0.69147\n",
      "[11]\tvalid_0's l1: 0.498024\tvalid_0's binary_logloss: 0.691048\n",
      "[12]\tvalid_0's l1: 0.497763\tvalid_0's binary_logloss: 0.690704\n",
      "[13]\tvalid_0's l1: 0.497441\tvalid_0's binary_logloss: 0.690285\n",
      "[14]\tvalid_0's l1: 0.497088\tvalid_0's binary_logloss: 0.6898\n",
      "[15]\tvalid_0's l1: 0.496962\tvalid_0's binary_logloss: 0.689592\n",
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      "[17]\tvalid_0's l1: 0.49667\tvalid_0's binary_logloss: 0.689255\n",
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      "[40]\tvalid_0's l1: 0.493287\tvalid_0's binary_logloss: 0.685873\n",
      "[41]\tvalid_0's l1: 0.493129\tvalid_0's binary_logloss: 0.685689\n",
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      "[43]\tvalid_0's l1: 0.492794\tvalid_0's binary_logloss: 0.685442\n",
      "[44]\tvalid_0's l1: 0.492687\tvalid_0's binary_logloss: 0.685416\n",
      "[45]\tvalid_0's l1: 0.492525\tvalid_0's binary_logloss: 0.685228\n",
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      "[47]\tvalid_0's l1: 0.492135\tvalid_0's binary_logloss: 0.684837\n",
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      "[57]\tvalid_0's l1: 0.490115\tvalid_0's binary_logloss: 0.683203\n",
      "[58]\tvalid_0's l1: 0.489855\tvalid_0's binary_logloss: 0.682936\n",
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      "[64]\tvalid_0's l1: 0.488804\tvalid_0's binary_logloss: 0.682455\n",
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      "[66]\tvalid_0's l1: 0.488327\tvalid_0's binary_logloss: 0.681987\n",
      "[67]\tvalid_0's l1: 0.488279\tvalid_0's binary_logloss: 0.682109\n",
      "[68]\tvalid_0's l1: 0.487967\tvalid_0's binary_logloss: 0.681775\n",
      "[69]\tvalid_0's l1: 0.487892\tvalid_0's binary_logloss: 0.681866\n",
      "[70]\tvalid_0's l1: 0.487755\tvalid_0's binary_logloss: 0.681815\n",
      "[71]\tvalid_0's l1: 0.487754\tvalid_0's binary_logloss: 0.682011\n",
      "[72]\tvalid_0's l1: 0.487562\tvalid_0's binary_logloss: 0.681882\n",
      "[73]\tvalid_0's l1: 0.487358\tvalid_0's binary_logloss: 0.681773\n",
      "[74]\tvalid_0's l1: 0.487137\tvalid_0's binary_logloss: 0.681544\n",
      "[75]\tvalid_0's l1: 0.487137\tvalid_0's binary_logloss: 0.681748\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[76]\tvalid_0's l1: 0.486949\tvalid_0's binary_logloss: 0.681641\n",
      "[77]\tvalid_0's l1: 0.486759\tvalid_0's binary_logloss: 0.681563\n",
      "[78]\tvalid_0's l1: 0.486587\tvalid_0's binary_logloss: 0.681461\n",
      "[79]\tvalid_0's l1: 0.48643\tvalid_0's binary_logloss: 0.68142\n",
      "[80]\tvalid_0's l1: 0.486259\tvalid_0's binary_logloss: 0.681207\n",
      "[81]\tvalid_0's l1: 0.486105\tvalid_0's binary_logloss: 0.681183\n",
      "[82]\tvalid_0's l1: 0.486051\tvalid_0's binary_logloss: 0.681228\n",
      "[83]\tvalid_0's l1: 0.485883\tvalid_0's binary_logloss: 0.681022\n",
      "[84]\tvalid_0's l1: 0.48575\tvalid_0's binary_logloss: 0.68106\n",
      "[85]\tvalid_0's l1: 0.485793\tvalid_0's binary_logloss: 0.681347\n",
      "[86]\tvalid_0's l1: 0.485762\tvalid_0's binary_logloss: 0.681429\n",
      "[87]\tvalid_0's l1: 0.485713\tvalid_0's binary_logloss: 0.681602\n",
      "[88]\tvalid_0's l1: 0.485548\tvalid_0's binary_logloss: 0.681403\n",
      "Early stopping, best iteration is:\n",
      "[83]\tvalid_0's l1: 0.485883\tvalid_0's binary_logloss: 0.681022\n",
      "[1]\tvalid_0's l1: 0.501148\tvalid_0's binary_logloss: 0.696029\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501018\tvalid_0's binary_logloss: 0.695742\n",
      "[3]\tvalid_0's l1: 0.500759\tvalid_0's binary_logloss: 0.695198\n",
      "[4]\tvalid_0's l1: 0.500583\tvalid_0's binary_logloss: 0.694829\n",
      "[5]\tvalid_0's l1: 0.500328\tvalid_0's binary_logloss: 0.694308\n",
      "[6]\tvalid_0's l1: 0.500154\tvalid_0's binary_logloss: 0.693954\n",
      "[7]\tvalid_0's l1: 0.499921\tvalid_0's binary_logloss: 0.693482\n",
      "[8]\tvalid_0's l1: 0.4997\tvalid_0's binary_logloss: 0.693048\n",
      "[9]\tvalid_0's l1: 0.49953\tvalid_0's binary_logloss: 0.692711\n",
      "[10]\tvalid_0's l1: 0.499335\tvalid_0's binary_logloss: 0.692334\n",
      "[11]\tvalid_0's l1: 0.499264\tvalid_0's binary_logloss: 0.692194\n",
      "[12]\tvalid_0's l1: 0.499051\tvalid_0's binary_logloss: 0.691787\n",
      "[13]\tvalid_0's l1: 0.498787\tvalid_0's binary_logloss: 0.691245\n",
      "[14]\tvalid_0's l1: 0.498622\tvalid_0's binary_logloss: 0.690931\n",
      "[15]\tvalid_0's l1: 0.498431\tvalid_0's binary_logloss: 0.690585\n",
      "[16]\tvalid_0's l1: 0.498356\tvalid_0's binary_logloss: 0.690421\n",
      "[17]\tvalid_0's l1: 0.498097\tvalid_0's binary_logloss: 0.689925\n",
      "[18]\tvalid_0's l1: 0.497834\tvalid_0's binary_logloss: 0.689402\n",
      "[19]\tvalid_0's l1: 0.497761\tvalid_0's binary_logloss: 0.689275\n",
      "[20]\tvalid_0's l1: 0.497534\tvalid_0's binary_logloss: 0.688864\n",
      "[21]\tvalid_0's l1: 0.497462\tvalid_0's binary_logloss: 0.688746\n",
      "[22]\tvalid_0's l1: 0.497391\tvalid_0's binary_logloss: 0.688613\n",
      "[23]\tvalid_0's l1: 0.497175\tvalid_0's binary_logloss: 0.688218\n",
      "[24]\tvalid_0's l1: 0.497106\tvalid_0's binary_logloss: 0.688113\n",
      "[25]\tvalid_0's l1: 0.496911\tvalid_0's binary_logloss: 0.687784\n",
      "[26]\tvalid_0's l1: 0.496695\tvalid_0's binary_logloss: 0.687374\n",
      "[27]\tvalid_0's l1: 0.496503\tvalid_0's binary_logloss: 0.687046\n",
      "[28]\tvalid_0's l1: 0.496301\tvalid_0's binary_logloss: 0.686705\n",
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      "[31]\tvalid_0's l1: 0.495839\tvalid_0's binary_logloss: 0.685909\n",
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      "[50]\tvalid_0's l1: 0.49285\tvalid_0's binary_logloss: 0.681469\n",
      "[51]\tvalid_0's l1: 0.492738\tvalid_0's binary_logloss: 0.681328\n",
      "[52]\tvalid_0's l1: 0.492632\tvalid_0's binary_logloss: 0.681128\n",
      "[53]\tvalid_0's l1: 0.492481\tvalid_0's binary_logloss: 0.681016\n",
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      "[55]\tvalid_0's l1: 0.492225\tvalid_0's binary_logloss: 0.680777\n",
      "[56]\tvalid_0's l1: 0.491968\tvalid_0's binary_logloss: 0.680371\n",
      "[57]\tvalid_0's l1: 0.491882\tvalid_0's binary_logloss: 0.680248\n",
      "[58]\tvalid_0's l1: 0.491774\tvalid_0's binary_logloss: 0.680215\n",
      "[59]\tvalid_0's l1: 0.491728\tvalid_0's binary_logloss: 0.680165\n",
      "[60]\tvalid_0's l1: 0.491645\tvalid_0's binary_logloss: 0.68005\n",
      "[61]\tvalid_0's l1: 0.49148\tvalid_0's binary_logloss: 0.679952\n",
      "[62]\tvalid_0's l1: 0.491407\tvalid_0's binary_logloss: 0.679855\n",
      "[63]\tvalid_0's l1: 0.491307\tvalid_0's binary_logloss: 0.67969\n",
      "[64]\tvalid_0's l1: 0.491202\tvalid_0's binary_logloss: 0.67968\n",
      "[65]\tvalid_0's l1: 0.491131\tvalid_0's binary_logloss: 0.679589\n",
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      "[67]\tvalid_0's l1: 0.490959\tvalid_0's binary_logloss: 0.679544\n",
      "[68]\tvalid_0's l1: 0.490821\tvalid_0's binary_logloss: 0.679316\n",
      "[69]\tvalid_0's l1: 0.490749\tvalid_0's binary_logloss: 0.679203\n",
      "[70]\tvalid_0's l1: 0.490629\tvalid_0's binary_logloss: 0.679181\n",
      "[71]\tvalid_0's l1: 0.490552\tvalid_0's binary_logloss: 0.679083\n",
      "[72]\tvalid_0's l1: 0.490472\tvalid_0's binary_logloss: 0.679104\n",
      "[73]\tvalid_0's l1: 0.490336\tvalid_0's binary_logloss: 0.678884\n",
      "[74]\tvalid_0's l1: 0.490212\tvalid_0's binary_logloss: 0.678899\n",
      "[75]\tvalid_0's l1: 0.490086\tvalid_0's binary_logloss: 0.6787\n",
      "[76]\tvalid_0's l1: 0.489975\tvalid_0's binary_logloss: 0.678733\n",
      "[77]\tvalid_0's l1: 0.48994\tvalid_0's binary_logloss: 0.678704\n",
      "[78]\tvalid_0's l1: 0.48985\tvalid_0's binary_logloss: 0.678745\n",
      "[79]\tvalid_0's l1: 0.489719\tvalid_0's binary_logloss: 0.678536\n",
      "[80]\tvalid_0's l1: 0.489581\tvalid_0's binary_logloss: 0.678555\n",
      "[81]\tvalid_0's l1: 0.489512\tvalid_0's binary_logloss: 0.678442\n",
      "[82]\tvalid_0's l1: 0.489478\tvalid_0's binary_logloss: 0.678418\n",
      "[83]\tvalid_0's l1: 0.48939\tvalid_0's binary_logloss: 0.678477\n",
      "[84]\tvalid_0's l1: 0.489398\tvalid_0's binary_logloss: 0.67858\n",
      "[85]\tvalid_0's l1: 0.489264\tvalid_0's binary_logloss: 0.678621\n",
      "[86]\tvalid_0's l1: 0.4891\tvalid_0's binary_logloss: 0.678342\n",
      "[87]\tvalid_0's l1: 0.488987\tvalid_0's binary_logloss: 0.678441\n",
      "[88]\tvalid_0's l1: 0.488952\tvalid_0's binary_logloss: 0.67842\n",
      "[89]\tvalid_0's l1: 0.488868\tvalid_0's binary_logloss: 0.678507\n",
      "[90]\tvalid_0's l1: 0.488706\tvalid_0's binary_logloss: 0.678235\n",
      "[91]\tvalid_0's l1: 0.488633\tvalid_0's binary_logloss: 0.678311\n",
      "[92]\tvalid_0's l1: 0.488572\tvalid_0's binary_logloss: 0.678208\n",
      "[93]\tvalid_0's l1: 0.488538\tvalid_0's binary_logloss: 0.678192\n",
      "[94]\tvalid_0's l1: 0.488478\tvalid_0's binary_logloss: 0.678366\n",
      "[95]\tvalid_0's l1: 0.488408\tvalid_0's binary_logloss: 0.678459\n",
      "[96]\tvalid_0's l1: 0.488365\tvalid_0's binary_logloss: 0.678426\n",
      "[97]\tvalid_0's l1: 0.488326\tvalid_0's binary_logloss: 0.678418\n",
      "[98]\tvalid_0's l1: 0.488265\tvalid_0's binary_logloss: 0.678637\n",
      "Early stopping, best iteration is:\n",
      "[93]\tvalid_0's l1: 0.488538\tvalid_0's binary_logloss: 0.678192\n",
      "[1]\tvalid_0's l1: 0.501167\tvalid_0's binary_logloss: 0.69602\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501005\tvalid_0's binary_logloss: 0.695667\n",
      "[3]\tvalid_0's l1: 0.500881\tvalid_0's binary_logloss: 0.6954\n",
      "[4]\tvalid_0's l1: 0.500739\tvalid_0's binary_logloss: 0.695106\n",
      "[5]\tvalid_0's l1: 0.500741\tvalid_0's binary_logloss: 0.695112\n",
      "[6]\tvalid_0's l1: 0.500663\tvalid_0's binary_logloss: 0.694968\n",
      "[7]\tvalid_0's l1: 0.500524\tvalid_0's binary_logloss: 0.694701\n",
      "[8]\tvalid_0's l1: 0.500595\tvalid_0's binary_logloss: 0.694829\n",
      "[9]\tvalid_0's l1: 0.500457\tvalid_0's binary_logloss: 0.694579\n",
      "[10]\tvalid_0's l1: 0.500527\tvalid_0's binary_logloss: 0.694722\n",
      "[11]\tvalid_0's l1: 0.500597\tvalid_0's binary_logloss: 0.69488\n",
      "[12]\tvalid_0's l1: 0.500596\tvalid_0's binary_logloss: 0.69489\n",
      "[13]\tvalid_0's l1: 0.500604\tvalid_0's binary_logloss: 0.694917\n",
      "[14]\tvalid_0's l1: 0.500528\tvalid_0's binary_logloss: 0.694815\n",
      "Early stopping, best iteration is:\n",
      "[9]\tvalid_0's l1: 0.500457\tvalid_0's binary_logloss: 0.694579\n",
      "[1]\tvalid_0's l1: 0.501\tvalid_0's binary_logloss: 0.69567\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500713\tvalid_0's binary_logloss: 0.695054\n",
      "[3]\tvalid_0's l1: 0.500464\tvalid_0's binary_logloss: 0.694519\n",
      "[4]\tvalid_0's l1: 0.500188\tvalid_0's binary_logloss: 0.693957\n",
      "[5]\tvalid_0's l1: 0.499944\tvalid_0's binary_logloss: 0.693465\n",
      "[6]\tvalid_0's l1: 0.499667\tvalid_0's binary_logloss: 0.692926\n",
      "[7]\tvalid_0's l1: 0.49937\tvalid_0's binary_logloss: 0.69236\n",
      "[8]\tvalid_0's l1: 0.499134\tvalid_0's binary_logloss: 0.691952\n",
      "[9]\tvalid_0's l1: 0.498876\tvalid_0's binary_logloss: 0.691491\n",
      "[10]\tvalid_0's l1: 0.498836\tvalid_0's binary_logloss: 0.691477\n",
      "[11]\tvalid_0's l1: 0.498797\tvalid_0's binary_logloss: 0.691473\n",
      "[12]\tvalid_0's l1: 0.498558\tvalid_0's binary_logloss: 0.691095\n",
      "[13]\tvalid_0's l1: 0.498519\tvalid_0's binary_logloss: 0.691106\n",
      "[14]\tvalid_0's l1: 0.498529\tvalid_0's binary_logloss: 0.691213\n",
      "[15]\tvalid_0's l1: 0.498514\tvalid_0's binary_logloss: 0.691266\n",
      "[16]\tvalid_0's l1: 0.498477\tvalid_0's binary_logloss: 0.6913\n",
      "[17]\tvalid_0's l1: 0.498462\tvalid_0's binary_logloss: 0.691367\n",
      "Early stopping, best iteration is:\n",
      "[12]\tvalid_0's l1: 0.498558\tvalid_0's binary_logloss: 0.691095\n",
      "[1]\tvalid_0's l1: 0.501151\tvalid_0's binary_logloss: 0.695996\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501011\tvalid_0's binary_logloss: 0.695693\n",
      "[3]\tvalid_0's l1: 0.500896\tvalid_0's binary_logloss: 0.695471\n",
      "[4]\tvalid_0's l1: 0.500764\tvalid_0's binary_logloss: 0.695216\n",
      "[5]\tvalid_0's l1: 0.500666\tvalid_0's binary_logloss: 0.695011\n",
      "[6]\tvalid_0's l1: 0.500574\tvalid_0's binary_logloss: 0.694842\n",
      "[7]\tvalid_0's l1: 0.500439\tvalid_0's binary_logloss: 0.694615\n",
      "[8]\tvalid_0's l1: 0.500349\tvalid_0's binary_logloss: 0.69448\n",
      "[9]\tvalid_0's l1: 0.500216\tvalid_0's binary_logloss: 0.694282\n",
      "[10]\tvalid_0's l1: 0.500128\tvalid_0's binary_logloss: 0.694178\n",
      "[11]\tvalid_0's l1: 0.499997\tvalid_0's binary_logloss: 0.694003\n",
      "[12]\tvalid_0's l1: 0.499743\tvalid_0's binary_logloss: 0.693574\n",
      "[13]\tvalid_0's l1: 0.499709\tvalid_0's binary_logloss: 0.693613\n",
      "[14]\tvalid_0's l1: 0.499633\tvalid_0's binary_logloss: 0.693562\n",
      "[15]\tvalid_0's l1: 0.499333\tvalid_0's binary_logloss: 0.693069\n",
      "[16]\tvalid_0's l1: 0.499208\tvalid_0's binary_logloss: 0.692945\n",
      "[17]\tvalid_0's l1: 0.49894\tvalid_0's binary_logloss: 0.692533\n",
      "[18]\tvalid_0's l1: 0.49882\tvalid_0's binary_logloss: 0.692449\n",
      "[19]\tvalid_0's l1: 0.498762\tvalid_0's binary_logloss: 0.692352\n",
      "[20]\tvalid_0's l1: 0.498711\tvalid_0's binary_logloss: 0.692386\n",
      "[21]\tvalid_0's l1: 0.498511\tvalid_0's binary_logloss: 0.692153\n",
      "[22]\tvalid_0's l1: 0.498434\tvalid_0's binary_logloss: 0.692038\n",
      "[23]\tvalid_0's l1: 0.498177\tvalid_0's binary_logloss: 0.691715\n",
      "[24]\tvalid_0's l1: 0.49812\tvalid_0's binary_logloss: 0.691655\n",
      "[25]\tvalid_0's l1: 0.498046\tvalid_0's binary_logloss: 0.691571\n",
      "[26]\tvalid_0's l1: 0.497846\tvalid_0's binary_logloss: 0.691384\n",
      "[27]\tvalid_0's l1: 0.497775\tvalid_0's binary_logloss: 0.691314\n",
      "[28]\tvalid_0's l1: 0.497474\tvalid_0's binary_logloss: 0.69092\n",
      "[29]\tvalid_0's l1: 0.497386\tvalid_0's binary_logloss: 0.690832\n",
      "[30]\tvalid_0's l1: 0.497191\tvalid_0's binary_logloss: 0.690685\n",
      "[31]\tvalid_0's l1: 0.497005\tvalid_0's binary_logloss: 0.690439\n",
      "[32]\tvalid_0's l1: 0.496917\tvalid_0's binary_logloss: 0.690368\n",
      "[33]\tvalid_0's l1: 0.496802\tvalid_0's binary_logloss: 0.690372\n",
      "[34]\tvalid_0's l1: 0.496623\tvalid_0's binary_logloss: 0.690177\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[35]\tvalid_0's l1: 0.496428\tvalid_0's binary_logloss: 0.690062\n",
      "[36]\tvalid_0's l1: 0.496326\tvalid_0's binary_logloss: 0.689969\n",
      "[37]\tvalid_0's l1: 0.496215\tvalid_0's binary_logloss: 0.689999\n",
      "[38]\tvalid_0's l1: 0.496157\tvalid_0's binary_logloss: 0.690096\n",
      "[39]\tvalid_0's l1: 0.496077\tvalid_0's binary_logloss: 0.690131\n",
      "[40]\tvalid_0's l1: 0.495973\tvalid_0's binary_logloss: 0.690172\n",
      "[41]\tvalid_0's l1: 0.495873\tvalid_0's binary_logloss: 0.690099\n",
      "Early stopping, best iteration is:\n",
      "[36]\tvalid_0's l1: 0.496326\tvalid_0's binary_logloss: 0.689969\n",
      "[1]\tvalid_0's l1: 0.501038\tvalid_0's binary_logloss: 0.695867\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500707\tvalid_0's binary_logloss: 0.695249\n",
      "[3]\tvalid_0's l1: 0.50038\tvalid_0's binary_logloss: 0.694654\n",
      "[4]\tvalid_0's l1: 0.500074\tvalid_0's binary_logloss: 0.694127\n",
      "[5]\tvalid_0's l1: 0.499753\tvalid_0's binary_logloss: 0.693579\n",
      "[6]\tvalid_0's l1: 0.49947\tvalid_0's binary_logloss: 0.693134\n",
      "[7]\tvalid_0's l1: 0.499172\tvalid_0's binary_logloss: 0.692678\n",
      "[8]\tvalid_0's l1: 0.498909\tvalid_0's binary_logloss: 0.692287\n",
      "[9]\tvalid_0's l1: 0.498618\tvalid_0's binary_logloss: 0.691857\n",
      "[10]\tvalid_0's l1: 0.498334\tvalid_0's binary_logloss: 0.69147\n",
      "[11]\tvalid_0's l1: 0.498024\tvalid_0's binary_logloss: 0.691048\n",
      "[12]\tvalid_0's l1: 0.497763\tvalid_0's binary_logloss: 0.690704\n",
      "[13]\tvalid_0's l1: 0.497441\tvalid_0's binary_logloss: 0.690285\n",
      "[14]\tvalid_0's l1: 0.497088\tvalid_0's binary_logloss: 0.6898\n",
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      "[16]\tvalid_0's l1: 0.496837\tvalid_0's binary_logloss: 0.689402\n",
      "[17]\tvalid_0's l1: 0.49667\tvalid_0's binary_logloss: 0.689255\n",
      "[18]\tvalid_0's l1: 0.496527\tvalid_0's binary_logloss: 0.689019\n",
      "[19]\tvalid_0's l1: 0.496326\tvalid_0's binary_logloss: 0.68884\n",
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      "[25]\tvalid_0's l1: 0.495454\tvalid_0's binary_logloss: 0.687998\n",
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      "[32]\tvalid_0's l1: 0.494374\tvalid_0's binary_logloss: 0.686762\n",
      "[33]\tvalid_0's l1: 0.494207\tvalid_0's binary_logloss: 0.686518\n",
      "[34]\tvalid_0's l1: 0.494042\tvalid_0's binary_logloss: 0.686287\n",
      "[35]\tvalid_0's l1: 0.493944\tvalid_0's binary_logloss: 0.686254\n",
      "[36]\tvalid_0's l1: 0.493781\tvalid_0's binary_logloss: 0.686039\n",
      "[37]\tvalid_0's l1: 0.493683\tvalid_0's binary_logloss: 0.686053\n",
      "[38]\tvalid_0's l1: 0.493547\tvalid_0's binary_logloss: 0.68606\n",
      "[39]\tvalid_0's l1: 0.49344\tvalid_0's binary_logloss: 0.686041\n",
      "[40]\tvalid_0's l1: 0.493287\tvalid_0's binary_logloss: 0.685873\n",
      "[41]\tvalid_0's l1: 0.493129\tvalid_0's binary_logloss: 0.685689\n",
      "[42]\tvalid_0's l1: 0.493049\tvalid_0's binary_logloss: 0.685751\n",
      "[43]\tvalid_0's l1: 0.492794\tvalid_0's binary_logloss: 0.685442\n",
      "[44]\tvalid_0's l1: 0.492687\tvalid_0's binary_logloss: 0.685416\n",
      "[45]\tvalid_0's l1: 0.492525\tvalid_0's binary_logloss: 0.685228\n",
      "[46]\tvalid_0's l1: 0.492288\tvalid_0's binary_logloss: 0.684912\n",
      "[47]\tvalid_0's l1: 0.492135\tvalid_0's binary_logloss: 0.684837\n",
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      "[49]\tvalid_0's l1: 0.491739\tvalid_0's binary_logloss: 0.6845\n",
      "[50]\tvalid_0's l1: 0.491601\tvalid_0's binary_logloss: 0.684476\n",
      "[51]\tvalid_0's l1: 0.49132\tvalid_0's binary_logloss: 0.684125\n",
      "[52]\tvalid_0's l1: 0.491049\tvalid_0's binary_logloss: 0.683799\n",
      "[53]\tvalid_0's l1: 0.490913\tvalid_0's binary_logloss: 0.683792\n",
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      "[55]\tvalid_0's l1: 0.490533\tvalid_0's binary_logloss: 0.683525\n",
      "[56]\tvalid_0's l1: 0.4904\tvalid_0's binary_logloss: 0.683533\n",
      "[57]\tvalid_0's l1: 0.490115\tvalid_0's binary_logloss: 0.683203\n",
      "[58]\tvalid_0's l1: 0.489855\tvalid_0's binary_logloss: 0.682936\n",
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      "[61]\tvalid_0's l1: 0.489349\tvalid_0's binary_logloss: 0.682799\n",
      "[62]\tvalid_0's l1: 0.489014\tvalid_0's binary_logloss: 0.682413\n",
      "[63]\tvalid_0's l1: 0.4889\tvalid_0's binary_logloss: 0.682375\n",
      "[64]\tvalid_0's l1: 0.488804\tvalid_0's binary_logloss: 0.682455\n",
      "[65]\tvalid_0's l1: 0.488469\tvalid_0's binary_logloss: 0.682062\n",
      "[66]\tvalid_0's l1: 0.488327\tvalid_0's binary_logloss: 0.681987\n",
      "[67]\tvalid_0's l1: 0.488279\tvalid_0's binary_logloss: 0.682109\n",
      "[68]\tvalid_0's l1: 0.487967\tvalid_0's binary_logloss: 0.681775\n",
      "[69]\tvalid_0's l1: 0.487892\tvalid_0's binary_logloss: 0.681866\n",
      "[70]\tvalid_0's l1: 0.487755\tvalid_0's binary_logloss: 0.681815\n",
      "[71]\tvalid_0's l1: 0.487754\tvalid_0's binary_logloss: 0.682011\n",
      "[72]\tvalid_0's l1: 0.487562\tvalid_0's binary_logloss: 0.681882\n",
      "[73]\tvalid_0's l1: 0.487358\tvalid_0's binary_logloss: 0.681773\n",
      "[74]\tvalid_0's l1: 0.487137\tvalid_0's binary_logloss: 0.681544\n",
      "[75]\tvalid_0's l1: 0.487137\tvalid_0's binary_logloss: 0.681748\n",
      "[76]\tvalid_0's l1: 0.486949\tvalid_0's binary_logloss: 0.681641\n",
      "[77]\tvalid_0's l1: 0.486759\tvalid_0's binary_logloss: 0.681563\n",
      "[78]\tvalid_0's l1: 0.486587\tvalid_0's binary_logloss: 0.681461\n",
      "[79]\tvalid_0's l1: 0.48643\tvalid_0's binary_logloss: 0.68142\n",
      "[80]\tvalid_0's l1: 0.486259\tvalid_0's binary_logloss: 0.681207\n",
      "[81]\tvalid_0's l1: 0.486105\tvalid_0's binary_logloss: 0.681183\n",
      "[82]\tvalid_0's l1: 0.486051\tvalid_0's binary_logloss: 0.681228\n",
      "[83]\tvalid_0's l1: 0.485883\tvalid_0's binary_logloss: 0.681022\n",
      "[84]\tvalid_0's l1: 0.48575\tvalid_0's binary_logloss: 0.68106\n",
      "[85]\tvalid_0's l1: 0.485793\tvalid_0's binary_logloss: 0.681347\n",
      "[86]\tvalid_0's l1: 0.485762\tvalid_0's binary_logloss: 0.681429\n",
      "[87]\tvalid_0's l1: 0.485713\tvalid_0's binary_logloss: 0.681602\n",
      "[88]\tvalid_0's l1: 0.485548\tvalid_0's binary_logloss: 0.681403\n",
      "Early stopping, best iteration is:\n",
      "[83]\tvalid_0's l1: 0.485883\tvalid_0's binary_logloss: 0.681022\n",
      "[1]\tvalid_0's l1: 0.501148\tvalid_0's binary_logloss: 0.696029\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501018\tvalid_0's binary_logloss: 0.695742\n",
      "[3]\tvalid_0's l1: 0.500759\tvalid_0's binary_logloss: 0.695198\n",
      "[4]\tvalid_0's l1: 0.500583\tvalid_0's binary_logloss: 0.694829\n",
      "[5]\tvalid_0's l1: 0.500328\tvalid_0's binary_logloss: 0.694308\n",
      "[6]\tvalid_0's l1: 0.500154\tvalid_0's binary_logloss: 0.693954\n",
      "[7]\tvalid_0's l1: 0.499921\tvalid_0's binary_logloss: 0.693482\n",
      "[8]\tvalid_0's l1: 0.4997\tvalid_0's binary_logloss: 0.693048\n",
      "[9]\tvalid_0's l1: 0.49953\tvalid_0's binary_logloss: 0.692711\n",
      "[10]\tvalid_0's l1: 0.499335\tvalid_0's binary_logloss: 0.692334\n",
      "[11]\tvalid_0's l1: 0.499264\tvalid_0's binary_logloss: 0.692194\n",
      "[12]\tvalid_0's l1: 0.499051\tvalid_0's binary_logloss: 0.691787\n",
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      "[14]\tvalid_0's l1: 0.498622\tvalid_0's binary_logloss: 0.690931\n",
      "[15]\tvalid_0's l1: 0.498431\tvalid_0's binary_logloss: 0.690585\n",
      "[16]\tvalid_0's l1: 0.498356\tvalid_0's binary_logloss: 0.690421\n",
      "[17]\tvalid_0's l1: 0.498097\tvalid_0's binary_logloss: 0.689925\n",
      "[18]\tvalid_0's l1: 0.497834\tvalid_0's binary_logloss: 0.689402\n",
      "[19]\tvalid_0's l1: 0.497761\tvalid_0's binary_logloss: 0.689275\n",
      "[20]\tvalid_0's l1: 0.497534\tvalid_0's binary_logloss: 0.688864\n",
      "[21]\tvalid_0's l1: 0.497462\tvalid_0's binary_logloss: 0.688746\n",
      "[22]\tvalid_0's l1: 0.497391\tvalid_0's binary_logloss: 0.688613\n",
      "[23]\tvalid_0's l1: 0.497175\tvalid_0's binary_logloss: 0.688218\n",
      "[24]\tvalid_0's l1: 0.497106\tvalid_0's binary_logloss: 0.688113\n",
      "[25]\tvalid_0's l1: 0.496911\tvalid_0's binary_logloss: 0.687784\n",
      "[26]\tvalid_0's l1: 0.496695\tvalid_0's binary_logloss: 0.687374\n",
      "[27]\tvalid_0's l1: 0.496503\tvalid_0's binary_logloss: 0.687046\n",
      "[28]\tvalid_0's l1: 0.496301\tvalid_0's binary_logloss: 0.686705\n",
      "[29]\tvalid_0's l1: 0.496086\tvalid_0's binary_logloss: 0.686307\n",
      "[30]\tvalid_0's l1: 0.4959\tvalid_0's binary_logloss: 0.686001\n",
      "[31]\tvalid_0's l1: 0.495839\tvalid_0's binary_logloss: 0.685909\n",
      "[32]\tvalid_0's l1: 0.495622\tvalid_0's binary_logloss: 0.68555\n",
      "[33]\tvalid_0's l1: 0.495447\tvalid_0's binary_logloss: 0.685234\n",
      "[34]\tvalid_0's l1: 0.495214\tvalid_0's binary_logloss: 0.684832\n",
      "[35]\tvalid_0's l1: 0.49505\tvalid_0's binary_logloss: 0.68456\n",
      "[36]\tvalid_0's l1: 0.494872\tvalid_0's binary_logloss: 0.684259\n",
      "[37]\tvalid_0's l1: 0.494796\tvalid_0's binary_logloss: 0.684155\n",
      "[38]\tvalid_0's l1: 0.494627\tvalid_0's binary_logloss: 0.683897\n",
      "[39]\tvalid_0's l1: 0.49448\tvalid_0's binary_logloss: 0.683696\n",
      "[40]\tvalid_0's l1: 0.49436\tvalid_0's binary_logloss: 0.683506\n",
      "[41]\tvalid_0's l1: 0.494175\tvalid_0's binary_logloss: 0.683266\n",
      "[42]\tvalid_0's l1: 0.49398\tvalid_0's binary_logloss: 0.682937\n",
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      "[48]\tvalid_0's l1: 0.493021\tvalid_0's binary_logloss: 0.681727\n",
      "[49]\tvalid_0's l1: 0.492835\tvalid_0's binary_logloss: 0.681439\n",
      "[50]\tvalid_0's l1: 0.49285\tvalid_0's binary_logloss: 0.681469\n",
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      "[52]\tvalid_0's l1: 0.492632\tvalid_0's binary_logloss: 0.681128\n",
      "[53]\tvalid_0's l1: 0.492481\tvalid_0's binary_logloss: 0.681016\n",
      "[54]\tvalid_0's l1: 0.492395\tvalid_0's binary_logloss: 0.680909\n",
      "[55]\tvalid_0's l1: 0.492225\tvalid_0's binary_logloss: 0.680777\n",
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      "[57]\tvalid_0's l1: 0.491882\tvalid_0's binary_logloss: 0.680248\n",
      "[58]\tvalid_0's l1: 0.491774\tvalid_0's binary_logloss: 0.680215\n",
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      "[63]\tvalid_0's l1: 0.491307\tvalid_0's binary_logloss: 0.67969\n",
      "[64]\tvalid_0's l1: 0.491202\tvalid_0's binary_logloss: 0.67968\n",
      "[65]\tvalid_0's l1: 0.491131\tvalid_0's binary_logloss: 0.679589\n",
      "[66]\tvalid_0's l1: 0.490989\tvalid_0's binary_logloss: 0.679557\n",
      "[67]\tvalid_0's l1: 0.490959\tvalid_0's binary_logloss: 0.679544\n",
      "[68]\tvalid_0's l1: 0.490821\tvalid_0's binary_logloss: 0.679316\n",
      "[69]\tvalid_0's l1: 0.490749\tvalid_0's binary_logloss: 0.679203\n",
      "[70]\tvalid_0's l1: 0.490629\tvalid_0's binary_logloss: 0.679181\n",
      "[71]\tvalid_0's l1: 0.490552\tvalid_0's binary_logloss: 0.679083\n",
      "[72]\tvalid_0's l1: 0.490472\tvalid_0's binary_logloss: 0.679104\n",
      "[73]\tvalid_0's l1: 0.490336\tvalid_0's binary_logloss: 0.678884\n",
      "[74]\tvalid_0's l1: 0.490212\tvalid_0's binary_logloss: 0.678899\n",
      "[75]\tvalid_0's l1: 0.490086\tvalid_0's binary_logloss: 0.6787\n",
      "[76]\tvalid_0's l1: 0.489975\tvalid_0's binary_logloss: 0.678733\n",
      "[77]\tvalid_0's l1: 0.48994\tvalid_0's binary_logloss: 0.678704\n",
      "[78]\tvalid_0's l1: 0.48985\tvalid_0's binary_logloss: 0.678745\n",
      "[79]\tvalid_0's l1: 0.489719\tvalid_0's binary_logloss: 0.678536\n",
      "[80]\tvalid_0's l1: 0.489581\tvalid_0's binary_logloss: 0.678555\n",
      "[81]\tvalid_0's l1: 0.489512\tvalid_0's binary_logloss: 0.678442\n",
      "[82]\tvalid_0's l1: 0.489478\tvalid_0's binary_logloss: 0.678418\n",
      "[83]\tvalid_0's l1: 0.48939\tvalid_0's binary_logloss: 0.678477\n",
      "[84]\tvalid_0's l1: 0.489398\tvalid_0's binary_logloss: 0.67858\n",
      "[85]\tvalid_0's l1: 0.489264\tvalid_0's binary_logloss: 0.678621\n",
      "[86]\tvalid_0's l1: 0.4891\tvalid_0's binary_logloss: 0.678342\n",
      "[87]\tvalid_0's l1: 0.488987\tvalid_0's binary_logloss: 0.678441\n",
      "[88]\tvalid_0's l1: 0.488952\tvalid_0's binary_logloss: 0.67842\n",
      "[89]\tvalid_0's l1: 0.488868\tvalid_0's binary_logloss: 0.678507\n",
      "[90]\tvalid_0's l1: 0.488706\tvalid_0's binary_logloss: 0.678235\n",
      "[91]\tvalid_0's l1: 0.488633\tvalid_0's binary_logloss: 0.678311\n",
      "[92]\tvalid_0's l1: 0.488572\tvalid_0's binary_logloss: 0.678208\n",
      "[93]\tvalid_0's l1: 0.488538\tvalid_0's binary_logloss: 0.678192\n",
      "[94]\tvalid_0's l1: 0.488478\tvalid_0's binary_logloss: 0.678366\n",
      "[95]\tvalid_0's l1: 0.488408\tvalid_0's binary_logloss: 0.678459\n",
      "[96]\tvalid_0's l1: 0.488365\tvalid_0's binary_logloss: 0.678426\n",
      "[97]\tvalid_0's l1: 0.488326\tvalid_0's binary_logloss: 0.678418\n",
      "[98]\tvalid_0's l1: 0.488265\tvalid_0's binary_logloss: 0.678637\n",
      "Early stopping, best iteration is:\n",
      "[93]\tvalid_0's l1: 0.488538\tvalid_0's binary_logloss: 0.678192\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1]\tvalid_0's l1: 0.501167\tvalid_0's binary_logloss: 0.69602\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501005\tvalid_0's binary_logloss: 0.695667\n",
      "[3]\tvalid_0's l1: 0.500881\tvalid_0's binary_logloss: 0.6954\n",
      "[4]\tvalid_0's l1: 0.500739\tvalid_0's binary_logloss: 0.695106\n",
      "[5]\tvalid_0's l1: 0.500741\tvalid_0's binary_logloss: 0.695112\n",
      "[6]\tvalid_0's l1: 0.500663\tvalid_0's binary_logloss: 0.694968\n",
      "[7]\tvalid_0's l1: 0.500524\tvalid_0's binary_logloss: 0.694701\n",
      "[8]\tvalid_0's l1: 0.500595\tvalid_0's binary_logloss: 0.694829\n",
      "[9]\tvalid_0's l1: 0.500457\tvalid_0's binary_logloss: 0.694579\n",
      "[10]\tvalid_0's l1: 0.500527\tvalid_0's binary_logloss: 0.694722\n",
      "[11]\tvalid_0's l1: 0.500597\tvalid_0's binary_logloss: 0.69488\n",
      "[12]\tvalid_0's l1: 0.500596\tvalid_0's binary_logloss: 0.69489\n",
      "[13]\tvalid_0's l1: 0.500604\tvalid_0's binary_logloss: 0.694917\n",
      "[14]\tvalid_0's l1: 0.500528\tvalid_0's binary_logloss: 0.694815\n",
      "Early stopping, best iteration is:\n",
      "[9]\tvalid_0's l1: 0.500457\tvalid_0's binary_logloss: 0.694579\n",
      "[1]\tvalid_0's l1: 0.501\tvalid_0's binary_logloss: 0.69567\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500713\tvalid_0's binary_logloss: 0.695054\n",
      "[3]\tvalid_0's l1: 0.500464\tvalid_0's binary_logloss: 0.694519\n",
      "[4]\tvalid_0's l1: 0.500188\tvalid_0's binary_logloss: 0.693957\n",
      "[5]\tvalid_0's l1: 0.499944\tvalid_0's binary_logloss: 0.693465\n",
      "[6]\tvalid_0's l1: 0.499667\tvalid_0's binary_logloss: 0.692926\n",
      "[7]\tvalid_0's l1: 0.49937\tvalid_0's binary_logloss: 0.69236\n",
      "[8]\tvalid_0's l1: 0.499134\tvalid_0's binary_logloss: 0.691952\n",
      "[9]\tvalid_0's l1: 0.498876\tvalid_0's binary_logloss: 0.691491\n",
      "[10]\tvalid_0's l1: 0.498836\tvalid_0's binary_logloss: 0.691477\n",
      "[11]\tvalid_0's l1: 0.498797\tvalid_0's binary_logloss: 0.691473\n",
      "[12]\tvalid_0's l1: 0.498558\tvalid_0's binary_logloss: 0.691095\n",
      "[13]\tvalid_0's l1: 0.498519\tvalid_0's binary_logloss: 0.691106\n",
      "[14]\tvalid_0's l1: 0.498529\tvalid_0's binary_logloss: 0.691213\n",
      "[15]\tvalid_0's l1: 0.498514\tvalid_0's binary_logloss: 0.691266\n",
      "[16]\tvalid_0's l1: 0.498477\tvalid_0's binary_logloss: 0.6913\n",
      "[17]\tvalid_0's l1: 0.498462\tvalid_0's binary_logloss: 0.691367\n",
      "Early stopping, best iteration is:\n",
      "[12]\tvalid_0's l1: 0.498558\tvalid_0's binary_logloss: 0.691095\n",
      "[1]\tvalid_0's l1: 0.501151\tvalid_0's binary_logloss: 0.695996\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501011\tvalid_0's binary_logloss: 0.695693\n",
      "[3]\tvalid_0's l1: 0.500896\tvalid_0's binary_logloss: 0.695471\n",
      "[4]\tvalid_0's l1: 0.500764\tvalid_0's binary_logloss: 0.695216\n",
      "[5]\tvalid_0's l1: 0.500666\tvalid_0's binary_logloss: 0.695011\n",
      "[6]\tvalid_0's l1: 0.500574\tvalid_0's binary_logloss: 0.694842\n",
      "[7]\tvalid_0's l1: 0.500439\tvalid_0's binary_logloss: 0.694615\n",
      "[8]\tvalid_0's l1: 0.500349\tvalid_0's binary_logloss: 0.69448\n",
      "[9]\tvalid_0's l1: 0.500216\tvalid_0's binary_logloss: 0.694282\n",
      "[10]\tvalid_0's l1: 0.500128\tvalid_0's binary_logloss: 0.694178\n",
      "[11]\tvalid_0's l1: 0.499997\tvalid_0's binary_logloss: 0.694003\n",
      "[12]\tvalid_0's l1: 0.499743\tvalid_0's binary_logloss: 0.693574\n",
      "[13]\tvalid_0's l1: 0.499709\tvalid_0's binary_logloss: 0.693613\n",
      "[14]\tvalid_0's l1: 0.499633\tvalid_0's binary_logloss: 0.693562\n",
      "[15]\tvalid_0's l1: 0.499333\tvalid_0's binary_logloss: 0.693069\n",
      "[16]\tvalid_0's l1: 0.499208\tvalid_0's binary_logloss: 0.692945\n",
      "[17]\tvalid_0's l1: 0.49894\tvalid_0's binary_logloss: 0.692533\n",
      "[18]\tvalid_0's l1: 0.49882\tvalid_0's binary_logloss: 0.692449\n",
      "[19]\tvalid_0's l1: 0.498762\tvalid_0's binary_logloss: 0.692352\n",
      "[20]\tvalid_0's l1: 0.498711\tvalid_0's binary_logloss: 0.692386\n",
      "[21]\tvalid_0's l1: 0.498511\tvalid_0's binary_logloss: 0.692153\n",
      "[22]\tvalid_0's l1: 0.498434\tvalid_0's binary_logloss: 0.692038\n",
      "[23]\tvalid_0's l1: 0.498177\tvalid_0's binary_logloss: 0.691715\n",
      "[24]\tvalid_0's l1: 0.49812\tvalid_0's binary_logloss: 0.691655\n",
      "[25]\tvalid_0's l1: 0.498046\tvalid_0's binary_logloss: 0.691571\n",
      "[26]\tvalid_0's l1: 0.497846\tvalid_0's binary_logloss: 0.691384\n",
      "[27]\tvalid_0's l1: 0.497775\tvalid_0's binary_logloss: 0.691314\n",
      "[28]\tvalid_0's l1: 0.497474\tvalid_0's binary_logloss: 0.69092\n",
      "[29]\tvalid_0's l1: 0.497386\tvalid_0's binary_logloss: 0.690832\n",
      "[30]\tvalid_0's l1: 0.497191\tvalid_0's binary_logloss: 0.690685\n",
      "[31]\tvalid_0's l1: 0.497005\tvalid_0's binary_logloss: 0.690439\n",
      "[32]\tvalid_0's l1: 0.496917\tvalid_0's binary_logloss: 0.690368\n",
      "[33]\tvalid_0's l1: 0.496802\tvalid_0's binary_logloss: 0.690372\n",
      "[34]\tvalid_0's l1: 0.496623\tvalid_0's binary_logloss: 0.690177\n",
      "[35]\tvalid_0's l1: 0.496428\tvalid_0's binary_logloss: 0.690062\n",
      "[36]\tvalid_0's l1: 0.496326\tvalid_0's binary_logloss: 0.689969\n",
      "[37]\tvalid_0's l1: 0.496215\tvalid_0's binary_logloss: 0.689999\n",
      "[38]\tvalid_0's l1: 0.496157\tvalid_0's binary_logloss: 0.690096\n",
      "[39]\tvalid_0's l1: 0.496077\tvalid_0's binary_logloss: 0.690131\n",
      "[40]\tvalid_0's l1: 0.495973\tvalid_0's binary_logloss: 0.690172\n",
      "[41]\tvalid_0's l1: 0.495873\tvalid_0's binary_logloss: 0.690099\n",
      "Early stopping, best iteration is:\n",
      "[36]\tvalid_0's l1: 0.496326\tvalid_0's binary_logloss: 0.689969\n",
      "[1]\tvalid_0's l1: 0.501038\tvalid_0's binary_logloss: 0.695867\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500707\tvalid_0's binary_logloss: 0.695249\n",
      "[3]\tvalid_0's l1: 0.50038\tvalid_0's binary_logloss: 0.694654\n",
      "[4]\tvalid_0's l1: 0.500074\tvalid_0's binary_logloss: 0.694127\n",
      "[5]\tvalid_0's l1: 0.499753\tvalid_0's binary_logloss: 0.693579\n",
      "[6]\tvalid_0's l1: 0.49947\tvalid_0's binary_logloss: 0.693134\n",
      "[7]\tvalid_0's l1: 0.499172\tvalid_0's binary_logloss: 0.692678\n",
      "[8]\tvalid_0's l1: 0.498909\tvalid_0's binary_logloss: 0.692287\n",
      "[9]\tvalid_0's l1: 0.498618\tvalid_0's binary_logloss: 0.691857\n",
      "[10]\tvalid_0's l1: 0.498334\tvalid_0's binary_logloss: 0.69147\n",
      "[11]\tvalid_0's l1: 0.498024\tvalid_0's binary_logloss: 0.691048\n",
      "[12]\tvalid_0's l1: 0.497763\tvalid_0's binary_logloss: 0.690704\n",
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      "[14]\tvalid_0's l1: 0.497088\tvalid_0's binary_logloss: 0.6898\n",
      "[15]\tvalid_0's l1: 0.496962\tvalid_0's binary_logloss: 0.689592\n",
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      "[17]\tvalid_0's l1: 0.49667\tvalid_0's binary_logloss: 0.689255\n",
      "[18]\tvalid_0's l1: 0.496527\tvalid_0's binary_logloss: 0.689019\n",
      "[19]\tvalid_0's l1: 0.496326\tvalid_0's binary_logloss: 0.68884\n",
      "[20]\tvalid_0's l1: 0.496205\tvalid_0's binary_logloss: 0.688691\n",
      "[21]\tvalid_0's l1: 0.496086\tvalid_0's binary_logloss: 0.688559\n",
      "[22]\tvalid_0's l1: 0.495855\tvalid_0's binary_logloss: 0.688319\n",
      "[23]\tvalid_0's l1: 0.495747\tvalid_0's binary_logloss: 0.688238\n",
      "[24]\tvalid_0's l1: 0.495544\tvalid_0's binary_logloss: 0.688043\n",
      "[25]\tvalid_0's l1: 0.495454\tvalid_0's binary_logloss: 0.687998\n",
      "[26]\tvalid_0's l1: 0.495279\tvalid_0's binary_logloss: 0.687703\n",
      "[27]\tvalid_0's l1: 0.495147\tvalid_0's binary_logloss: 0.687556\n",
      "[28]\tvalid_0's l1: 0.494975\tvalid_0's binary_logloss: 0.687278\n",
      "[29]\tvalid_0's l1: 0.494714\tvalid_0's binary_logloss: 0.686849\n",
      "[30]\tvalid_0's l1: 0.494627\tvalid_0's binary_logloss: 0.686839\n",
      "[31]\tvalid_0's l1: 0.494486\tvalid_0's binary_logloss: 0.686817\n",
      "[32]\tvalid_0's l1: 0.494374\tvalid_0's binary_logloss: 0.686762\n",
      "[33]\tvalid_0's l1: 0.494207\tvalid_0's binary_logloss: 0.686518\n",
      "[34]\tvalid_0's l1: 0.494042\tvalid_0's binary_logloss: 0.686287\n",
      "[35]\tvalid_0's l1: 0.493944\tvalid_0's binary_logloss: 0.686254\n",
      "[36]\tvalid_0's l1: 0.493781\tvalid_0's binary_logloss: 0.686039\n",
      "[37]\tvalid_0's l1: 0.493683\tvalid_0's binary_logloss: 0.686053\n",
      "[38]\tvalid_0's l1: 0.493547\tvalid_0's binary_logloss: 0.68606\n",
      "[39]\tvalid_0's l1: 0.49344\tvalid_0's binary_logloss: 0.686041\n",
      "[40]\tvalid_0's l1: 0.493287\tvalid_0's binary_logloss: 0.685873\n",
      "[41]\tvalid_0's l1: 0.493129\tvalid_0's binary_logloss: 0.685689\n",
      "[42]\tvalid_0's l1: 0.493049\tvalid_0's binary_logloss: 0.685751\n",
      "[43]\tvalid_0's l1: 0.492794\tvalid_0's binary_logloss: 0.685442\n",
      "[44]\tvalid_0's l1: 0.492687\tvalid_0's binary_logloss: 0.685416\n",
      "[45]\tvalid_0's l1: 0.492525\tvalid_0's binary_logloss: 0.685228\n",
      "[46]\tvalid_0's l1: 0.492288\tvalid_0's binary_logloss: 0.684912\n",
      "[47]\tvalid_0's l1: 0.492135\tvalid_0's binary_logloss: 0.684837\n",
      "[48]\tvalid_0's l1: 0.491868\tvalid_0's binary_logloss: 0.684461\n",
      "[49]\tvalid_0's l1: 0.491739\tvalid_0's binary_logloss: 0.6845\n",
      "[50]\tvalid_0's l1: 0.491601\tvalid_0's binary_logloss: 0.684476\n",
      "[51]\tvalid_0's l1: 0.49132\tvalid_0's binary_logloss: 0.684125\n",
      "[52]\tvalid_0's l1: 0.491049\tvalid_0's binary_logloss: 0.683799\n",
      "[53]\tvalid_0's l1: 0.490913\tvalid_0's binary_logloss: 0.683792\n",
      "[54]\tvalid_0's l1: 0.490654\tvalid_0's binary_logloss: 0.683454\n",
      "[55]\tvalid_0's l1: 0.490533\tvalid_0's binary_logloss: 0.683525\n",
      "[56]\tvalid_0's l1: 0.4904\tvalid_0's binary_logloss: 0.683533\n",
      "[57]\tvalid_0's l1: 0.490115\tvalid_0's binary_logloss: 0.683203\n",
      "[58]\tvalid_0's l1: 0.489855\tvalid_0's binary_logloss: 0.682936\n",
      "[59]\tvalid_0's l1: 0.489738\tvalid_0's binary_logloss: 0.683029\n",
      "[60]\tvalid_0's l1: 0.489608\tvalid_0's binary_logloss: 0.683055\n",
      "[61]\tvalid_0's l1: 0.489349\tvalid_0's binary_logloss: 0.682799\n",
      "[62]\tvalid_0's l1: 0.489014\tvalid_0's binary_logloss: 0.682413\n",
      "[63]\tvalid_0's l1: 0.4889\tvalid_0's binary_logloss: 0.682375\n",
      "[64]\tvalid_0's l1: 0.488804\tvalid_0's binary_logloss: 0.682455\n",
      "[65]\tvalid_0's l1: 0.488469\tvalid_0's binary_logloss: 0.682062\n",
      "[66]\tvalid_0's l1: 0.488327\tvalid_0's binary_logloss: 0.681987\n",
      "[67]\tvalid_0's l1: 0.488279\tvalid_0's binary_logloss: 0.682109\n",
      "[68]\tvalid_0's l1: 0.487967\tvalid_0's binary_logloss: 0.681775\n",
      "[69]\tvalid_0's l1: 0.487892\tvalid_0's binary_logloss: 0.681866\n",
      "[70]\tvalid_0's l1: 0.487755\tvalid_0's binary_logloss: 0.681815\n",
      "[71]\tvalid_0's l1: 0.487754\tvalid_0's binary_logloss: 0.682011\n",
      "[72]\tvalid_0's l1: 0.487562\tvalid_0's binary_logloss: 0.681882\n",
      "[73]\tvalid_0's l1: 0.487358\tvalid_0's binary_logloss: 0.681773\n",
      "[74]\tvalid_0's l1: 0.487137\tvalid_0's binary_logloss: 0.681544\n",
      "[75]\tvalid_0's l1: 0.487137\tvalid_0's binary_logloss: 0.681748\n",
      "[76]\tvalid_0's l1: 0.486949\tvalid_0's binary_logloss: 0.681641\n",
      "[77]\tvalid_0's l1: 0.486759\tvalid_0's binary_logloss: 0.681563\n",
      "[78]\tvalid_0's l1: 0.486587\tvalid_0's binary_logloss: 0.681461\n",
      "[79]\tvalid_0's l1: 0.48643\tvalid_0's binary_logloss: 0.68142\n",
      "[80]\tvalid_0's l1: 0.486259\tvalid_0's binary_logloss: 0.681207\n",
      "[81]\tvalid_0's l1: 0.486105\tvalid_0's binary_logloss: 0.681183\n",
      "[82]\tvalid_0's l1: 0.486051\tvalid_0's binary_logloss: 0.681228\n",
      "[83]\tvalid_0's l1: 0.485883\tvalid_0's binary_logloss: 0.681022\n",
      "[84]\tvalid_0's l1: 0.48575\tvalid_0's binary_logloss: 0.68106\n",
      "[85]\tvalid_0's l1: 0.485793\tvalid_0's binary_logloss: 0.681347\n",
      "[86]\tvalid_0's l1: 0.485762\tvalid_0's binary_logloss: 0.681429\n",
      "[87]\tvalid_0's l1: 0.485713\tvalid_0's binary_logloss: 0.681602\n",
      "[88]\tvalid_0's l1: 0.485548\tvalid_0's binary_logloss: 0.681403\n",
      "Early stopping, best iteration is:\n",
      "[83]\tvalid_0's l1: 0.485883\tvalid_0's binary_logloss: 0.681022\n",
      "[1]\tvalid_0's l1: 0.501148\tvalid_0's binary_logloss: 0.696029\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501018\tvalid_0's binary_logloss: 0.695742\n",
      "[3]\tvalid_0's l1: 0.500759\tvalid_0's binary_logloss: 0.695198\n",
      "[4]\tvalid_0's l1: 0.500583\tvalid_0's binary_logloss: 0.694829\n",
      "[5]\tvalid_0's l1: 0.500328\tvalid_0's binary_logloss: 0.694308\n",
      "[6]\tvalid_0's l1: 0.500154\tvalid_0's binary_logloss: 0.693954\n",
      "[7]\tvalid_0's l1: 0.499921\tvalid_0's binary_logloss: 0.693482\n",
      "[8]\tvalid_0's l1: 0.4997\tvalid_0's binary_logloss: 0.693048\n",
      "[9]\tvalid_0's l1: 0.49953\tvalid_0's binary_logloss: 0.692711\n",
      "[10]\tvalid_0's l1: 0.499335\tvalid_0's binary_logloss: 0.692334\n",
      "[11]\tvalid_0's l1: 0.499264\tvalid_0's binary_logloss: 0.692194\n",
      "[12]\tvalid_0's l1: 0.499051\tvalid_0's binary_logloss: 0.691787\n",
      "[13]\tvalid_0's l1: 0.498787\tvalid_0's binary_logloss: 0.691245\n",
      "[14]\tvalid_0's l1: 0.498622\tvalid_0's binary_logloss: 0.690931\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[15]\tvalid_0's l1: 0.498431\tvalid_0's binary_logloss: 0.690585\n",
      "[16]\tvalid_0's l1: 0.498356\tvalid_0's binary_logloss: 0.690421\n",
      "[17]\tvalid_0's l1: 0.498097\tvalid_0's binary_logloss: 0.689925\n",
      "[18]\tvalid_0's l1: 0.497834\tvalid_0's binary_logloss: 0.689402\n",
      "[19]\tvalid_0's l1: 0.497761\tvalid_0's binary_logloss: 0.689275\n",
      "[20]\tvalid_0's l1: 0.497534\tvalid_0's binary_logloss: 0.688864\n",
      "[21]\tvalid_0's l1: 0.497462\tvalid_0's binary_logloss: 0.688746\n",
      "[22]\tvalid_0's l1: 0.497391\tvalid_0's binary_logloss: 0.688613\n",
      "[23]\tvalid_0's l1: 0.497175\tvalid_0's binary_logloss: 0.688218\n",
      "[24]\tvalid_0's l1: 0.497106\tvalid_0's binary_logloss: 0.688113\n",
      "[25]\tvalid_0's l1: 0.496911\tvalid_0's binary_logloss: 0.687784\n",
      "[26]\tvalid_0's l1: 0.496695\tvalid_0's binary_logloss: 0.687374\n",
      "[27]\tvalid_0's l1: 0.496503\tvalid_0's binary_logloss: 0.687046\n",
      "[28]\tvalid_0's l1: 0.496301\tvalid_0's binary_logloss: 0.686705\n",
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      "[30]\tvalid_0's l1: 0.4959\tvalid_0's binary_logloss: 0.686001\n",
      "[31]\tvalid_0's l1: 0.495839\tvalid_0's binary_logloss: 0.685909\n",
      "[32]\tvalid_0's l1: 0.495622\tvalid_0's binary_logloss: 0.68555\n",
      "[33]\tvalid_0's l1: 0.495447\tvalid_0's binary_logloss: 0.685234\n",
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      "[35]\tvalid_0's l1: 0.49505\tvalid_0's binary_logloss: 0.68456\n",
      "[36]\tvalid_0's l1: 0.494872\tvalid_0's binary_logloss: 0.684259\n",
      "[37]\tvalid_0's l1: 0.494796\tvalid_0's binary_logloss: 0.684155\n",
      "[38]\tvalid_0's l1: 0.494627\tvalid_0's binary_logloss: 0.683897\n",
      "[39]\tvalid_0's l1: 0.49448\tvalid_0's binary_logloss: 0.683696\n",
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      "[48]\tvalid_0's l1: 0.493021\tvalid_0's binary_logloss: 0.681727\n",
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      "[50]\tvalid_0's l1: 0.49285\tvalid_0's binary_logloss: 0.681469\n",
      "[51]\tvalid_0's l1: 0.492738\tvalid_0's binary_logloss: 0.681328\n",
      "[52]\tvalid_0's l1: 0.492632\tvalid_0's binary_logloss: 0.681128\n",
      "[53]\tvalid_0's l1: 0.492481\tvalid_0's binary_logloss: 0.681016\n",
      "[54]\tvalid_0's l1: 0.492395\tvalid_0's binary_logloss: 0.680909\n",
      "[55]\tvalid_0's l1: 0.492225\tvalid_0's binary_logloss: 0.680777\n",
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      "[57]\tvalid_0's l1: 0.491882\tvalid_0's binary_logloss: 0.680248\n",
      "[58]\tvalid_0's l1: 0.491774\tvalid_0's binary_logloss: 0.680215\n",
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      "[60]\tvalid_0's l1: 0.491645\tvalid_0's binary_logloss: 0.68005\n",
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      "[62]\tvalid_0's l1: 0.491407\tvalid_0's binary_logloss: 0.679855\n",
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      "[73]\tvalid_0's l1: 0.490336\tvalid_0's binary_logloss: 0.678884\n",
      "[74]\tvalid_0's l1: 0.490212\tvalid_0's binary_logloss: 0.678899\n",
      "[75]\tvalid_0's l1: 0.490086\tvalid_0's binary_logloss: 0.6787\n",
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      "[77]\tvalid_0's l1: 0.48994\tvalid_0's binary_logloss: 0.678704\n",
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      "[79]\tvalid_0's l1: 0.489719\tvalid_0's binary_logloss: 0.678536\n",
      "[80]\tvalid_0's l1: 0.489581\tvalid_0's binary_logloss: 0.678555\n",
      "[81]\tvalid_0's l1: 0.489512\tvalid_0's binary_logloss: 0.678442\n",
      "[82]\tvalid_0's l1: 0.489478\tvalid_0's binary_logloss: 0.678418\n",
      "[83]\tvalid_0's l1: 0.48939\tvalid_0's binary_logloss: 0.678477\n",
      "[84]\tvalid_0's l1: 0.489398\tvalid_0's binary_logloss: 0.67858\n",
      "[85]\tvalid_0's l1: 0.489264\tvalid_0's binary_logloss: 0.678621\n",
      "[86]\tvalid_0's l1: 0.4891\tvalid_0's binary_logloss: 0.678342\n",
      "[87]\tvalid_0's l1: 0.488987\tvalid_0's binary_logloss: 0.678441\n",
      "[88]\tvalid_0's l1: 0.488952\tvalid_0's binary_logloss: 0.67842\n",
      "[89]\tvalid_0's l1: 0.488868\tvalid_0's binary_logloss: 0.678507\n",
      "[90]\tvalid_0's l1: 0.488706\tvalid_0's binary_logloss: 0.678235\n",
      "[91]\tvalid_0's l1: 0.488633\tvalid_0's binary_logloss: 0.678311\n",
      "[92]\tvalid_0's l1: 0.488572\tvalid_0's binary_logloss: 0.678208\n",
      "[93]\tvalid_0's l1: 0.488538\tvalid_0's binary_logloss: 0.678192\n",
      "[94]\tvalid_0's l1: 0.488478\tvalid_0's binary_logloss: 0.678366\n",
      "[95]\tvalid_0's l1: 0.488408\tvalid_0's binary_logloss: 0.678459\n",
      "[96]\tvalid_0's l1: 0.488365\tvalid_0's binary_logloss: 0.678426\n",
      "[97]\tvalid_0's l1: 0.488326\tvalid_0's binary_logloss: 0.678418\n",
      "[98]\tvalid_0's l1: 0.488265\tvalid_0's binary_logloss: 0.678637\n",
      "Early stopping, best iteration is:\n",
      "[93]\tvalid_0's l1: 0.488538\tvalid_0's binary_logloss: 0.678192\n",
      "[1]\tvalid_0's l1: 0.501167\tvalid_0's binary_logloss: 0.69602\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501005\tvalid_0's binary_logloss: 0.695667\n",
      "[3]\tvalid_0's l1: 0.500881\tvalid_0's binary_logloss: 0.6954\n",
      "[4]\tvalid_0's l1: 0.500739\tvalid_0's binary_logloss: 0.695106\n",
      "[5]\tvalid_0's l1: 0.500741\tvalid_0's binary_logloss: 0.695112\n",
      "[6]\tvalid_0's l1: 0.500663\tvalid_0's binary_logloss: 0.694968\n",
      "[7]\tvalid_0's l1: 0.500524\tvalid_0's binary_logloss: 0.694701\n",
      "[8]\tvalid_0's l1: 0.500595\tvalid_0's binary_logloss: 0.694829\n",
      "[9]\tvalid_0's l1: 0.500457\tvalid_0's binary_logloss: 0.694579\n",
      "[10]\tvalid_0's l1: 0.500527\tvalid_0's binary_logloss: 0.694722\n",
      "[11]\tvalid_0's l1: 0.500597\tvalid_0's binary_logloss: 0.69488\n",
      "[12]\tvalid_0's l1: 0.500596\tvalid_0's binary_logloss: 0.69489\n",
      "[13]\tvalid_0's l1: 0.500604\tvalid_0's binary_logloss: 0.694917\n",
      "[14]\tvalid_0's l1: 0.500528\tvalid_0's binary_logloss: 0.694815\n",
      "Early stopping, best iteration is:\n",
      "[9]\tvalid_0's l1: 0.500457\tvalid_0's binary_logloss: 0.694579\n",
      "[1]\tvalid_0's l1: 0.501\tvalid_0's binary_logloss: 0.69567\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500713\tvalid_0's binary_logloss: 0.695054\n",
      "[3]\tvalid_0's l1: 0.500464\tvalid_0's binary_logloss: 0.694519\n",
      "[4]\tvalid_0's l1: 0.500188\tvalid_0's binary_logloss: 0.693957\n",
      "[5]\tvalid_0's l1: 0.499944\tvalid_0's binary_logloss: 0.693465\n",
      "[6]\tvalid_0's l1: 0.499667\tvalid_0's binary_logloss: 0.692926\n",
      "[7]\tvalid_0's l1: 0.49937\tvalid_0's binary_logloss: 0.69236\n",
      "[8]\tvalid_0's l1: 0.499134\tvalid_0's binary_logloss: 0.691952\n",
      "[9]\tvalid_0's l1: 0.498876\tvalid_0's binary_logloss: 0.691491\n",
      "[10]\tvalid_0's l1: 0.498836\tvalid_0's binary_logloss: 0.691477\n",
      "[11]\tvalid_0's l1: 0.498797\tvalid_0's binary_logloss: 0.691473\n",
      "[12]\tvalid_0's l1: 0.498558\tvalid_0's binary_logloss: 0.691095\n",
      "[13]\tvalid_0's l1: 0.498519\tvalid_0's binary_logloss: 0.691106\n",
      "[14]\tvalid_0's l1: 0.498529\tvalid_0's binary_logloss: 0.691213\n",
      "[15]\tvalid_0's l1: 0.498514\tvalid_0's binary_logloss: 0.691266\n",
      "[16]\tvalid_0's l1: 0.498477\tvalid_0's binary_logloss: 0.6913\n",
      "[17]\tvalid_0's l1: 0.498462\tvalid_0's binary_logloss: 0.691367\n",
      "Early stopping, best iteration is:\n",
      "[12]\tvalid_0's l1: 0.498558\tvalid_0's binary_logloss: 0.691095\n",
      "[1]\tvalid_0's l1: 0.501151\tvalid_0's binary_logloss: 0.695996\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501011\tvalid_0's binary_logloss: 0.695693\n",
      "[3]\tvalid_0's l1: 0.500896\tvalid_0's binary_logloss: 0.695471\n",
      "[4]\tvalid_0's l1: 0.500764\tvalid_0's binary_logloss: 0.695216\n",
      "[5]\tvalid_0's l1: 0.500666\tvalid_0's binary_logloss: 0.695011\n",
      "[6]\tvalid_0's l1: 0.500574\tvalid_0's binary_logloss: 0.694842\n",
      "[7]\tvalid_0's l1: 0.500439\tvalid_0's binary_logloss: 0.694615\n",
      "[8]\tvalid_0's l1: 0.500349\tvalid_0's binary_logloss: 0.69448\n",
      "[9]\tvalid_0's l1: 0.500216\tvalid_0's binary_logloss: 0.694282\n",
      "[10]\tvalid_0's l1: 0.500128\tvalid_0's binary_logloss: 0.694178\n",
      "[11]\tvalid_0's l1: 0.499997\tvalid_0's binary_logloss: 0.694003\n",
      "[12]\tvalid_0's l1: 0.499743\tvalid_0's binary_logloss: 0.693574\n",
      "[13]\tvalid_0's l1: 0.499709\tvalid_0's binary_logloss: 0.693613\n",
      "[14]\tvalid_0's l1: 0.499633\tvalid_0's binary_logloss: 0.693562\n",
      "[15]\tvalid_0's l1: 0.499333\tvalid_0's binary_logloss: 0.693069\n",
      "[16]\tvalid_0's l1: 0.499208\tvalid_0's binary_logloss: 0.692945\n",
      "[17]\tvalid_0's l1: 0.49894\tvalid_0's binary_logloss: 0.692533\n",
      "[18]\tvalid_0's l1: 0.49882\tvalid_0's binary_logloss: 0.692449\n",
      "[19]\tvalid_0's l1: 0.498762\tvalid_0's binary_logloss: 0.692352\n",
      "[20]\tvalid_0's l1: 0.498711\tvalid_0's binary_logloss: 0.692386\n",
      "[21]\tvalid_0's l1: 0.498511\tvalid_0's binary_logloss: 0.692153\n",
      "[22]\tvalid_0's l1: 0.498434\tvalid_0's binary_logloss: 0.692038\n",
      "[23]\tvalid_0's l1: 0.498177\tvalid_0's binary_logloss: 0.691715\n",
      "[24]\tvalid_0's l1: 0.49812\tvalid_0's binary_logloss: 0.691655\n",
      "[25]\tvalid_0's l1: 0.498046\tvalid_0's binary_logloss: 0.691571\n",
      "[26]\tvalid_0's l1: 0.497846\tvalid_0's binary_logloss: 0.691384\n",
      "[27]\tvalid_0's l1: 0.497775\tvalid_0's binary_logloss: 0.691314\n",
      "[28]\tvalid_0's l1: 0.497474\tvalid_0's binary_logloss: 0.69092\n",
      "[29]\tvalid_0's l1: 0.497386\tvalid_0's binary_logloss: 0.690832\n",
      "[30]\tvalid_0's l1: 0.497191\tvalid_0's binary_logloss: 0.690685\n",
      "[31]\tvalid_0's l1: 0.497005\tvalid_0's binary_logloss: 0.690439\n",
      "[32]\tvalid_0's l1: 0.496917\tvalid_0's binary_logloss: 0.690368\n",
      "[33]\tvalid_0's l1: 0.496802\tvalid_0's binary_logloss: 0.690372\n",
      "[34]\tvalid_0's l1: 0.496623\tvalid_0's binary_logloss: 0.690177\n",
      "[35]\tvalid_0's l1: 0.496428\tvalid_0's binary_logloss: 0.690062\n",
      "[36]\tvalid_0's l1: 0.496326\tvalid_0's binary_logloss: 0.689969\n",
      "[37]\tvalid_0's l1: 0.496215\tvalid_0's binary_logloss: 0.689999\n",
      "[38]\tvalid_0's l1: 0.496157\tvalid_0's binary_logloss: 0.690096\n",
      "[39]\tvalid_0's l1: 0.496077\tvalid_0's binary_logloss: 0.690131\n",
      "[40]\tvalid_0's l1: 0.495973\tvalid_0's binary_logloss: 0.690172\n",
      "[41]\tvalid_0's l1: 0.495873\tvalid_0's binary_logloss: 0.690099\n",
      "Early stopping, best iteration is:\n",
      "[36]\tvalid_0's l1: 0.496326\tvalid_0's binary_logloss: 0.689969\n",
      "[1]\tvalid_0's l1: 0.501038\tvalid_0's binary_logloss: 0.695867\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500707\tvalid_0's binary_logloss: 0.695249\n",
      "[3]\tvalid_0's l1: 0.50038\tvalid_0's binary_logloss: 0.694654\n",
      "[4]\tvalid_0's l1: 0.500074\tvalid_0's binary_logloss: 0.694127\n",
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      "[6]\tvalid_0's l1: 0.49947\tvalid_0's binary_logloss: 0.693134\n",
      "[7]\tvalid_0's l1: 0.499172\tvalid_0's binary_logloss: 0.692678\n",
      "[8]\tvalid_0's l1: 0.498909\tvalid_0's binary_logloss: 0.692287\n",
      "[9]\tvalid_0's l1: 0.498618\tvalid_0's binary_logloss: 0.691857\n",
      "[10]\tvalid_0's l1: 0.498334\tvalid_0's binary_logloss: 0.69147\n",
      "[11]\tvalid_0's l1: 0.498024\tvalid_0's binary_logloss: 0.691048\n",
      "[12]\tvalid_0's l1: 0.497763\tvalid_0's binary_logloss: 0.690704\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[13]\tvalid_0's l1: 0.497441\tvalid_0's binary_logloss: 0.690285\n",
      "[14]\tvalid_0's l1: 0.497088\tvalid_0's binary_logloss: 0.6898\n",
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      "[50]\tvalid_0's l1: 0.491601\tvalid_0's binary_logloss: 0.684476\n",
      "[51]\tvalid_0's l1: 0.49132\tvalid_0's binary_logloss: 0.684125\n",
      "[52]\tvalid_0's l1: 0.491049\tvalid_0's binary_logloss: 0.683799\n",
      "[53]\tvalid_0's l1: 0.490913\tvalid_0's binary_logloss: 0.683792\n",
      "[54]\tvalid_0's l1: 0.490654\tvalid_0's binary_logloss: 0.683454\n",
      "[55]\tvalid_0's l1: 0.490533\tvalid_0's binary_logloss: 0.683525\n",
      "[56]\tvalid_0's l1: 0.4904\tvalid_0's binary_logloss: 0.683533\n",
      "[57]\tvalid_0's l1: 0.490115\tvalid_0's binary_logloss: 0.683203\n",
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      "[62]\tvalid_0's l1: 0.489014\tvalid_0's binary_logloss: 0.682413\n",
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      "[64]\tvalid_0's l1: 0.488804\tvalid_0's binary_logloss: 0.682455\n",
      "[65]\tvalid_0's l1: 0.488469\tvalid_0's binary_logloss: 0.682062\n",
      "[66]\tvalid_0's l1: 0.488327\tvalid_0's binary_logloss: 0.681987\n",
      "[67]\tvalid_0's l1: 0.488279\tvalid_0's binary_logloss: 0.682109\n",
      "[68]\tvalid_0's l1: 0.487967\tvalid_0's binary_logloss: 0.681775\n",
      "[69]\tvalid_0's l1: 0.487892\tvalid_0's binary_logloss: 0.681866\n",
      "[70]\tvalid_0's l1: 0.487755\tvalid_0's binary_logloss: 0.681815\n",
      "[71]\tvalid_0's l1: 0.487754\tvalid_0's binary_logloss: 0.682011\n",
      "[72]\tvalid_0's l1: 0.487562\tvalid_0's binary_logloss: 0.681882\n",
      "[73]\tvalid_0's l1: 0.487358\tvalid_0's binary_logloss: 0.681773\n",
      "[74]\tvalid_0's l1: 0.487137\tvalid_0's binary_logloss: 0.681544\n",
      "[75]\tvalid_0's l1: 0.487137\tvalid_0's binary_logloss: 0.681748\n",
      "[76]\tvalid_0's l1: 0.486949\tvalid_0's binary_logloss: 0.681641\n",
      "[77]\tvalid_0's l1: 0.486759\tvalid_0's binary_logloss: 0.681563\n",
      "[78]\tvalid_0's l1: 0.486587\tvalid_0's binary_logloss: 0.681461\n",
      "[79]\tvalid_0's l1: 0.48643\tvalid_0's binary_logloss: 0.68142\n",
      "[80]\tvalid_0's l1: 0.486259\tvalid_0's binary_logloss: 0.681207\n",
      "[81]\tvalid_0's l1: 0.486105\tvalid_0's binary_logloss: 0.681183\n",
      "[82]\tvalid_0's l1: 0.486051\tvalid_0's binary_logloss: 0.681228\n",
      "[83]\tvalid_0's l1: 0.485883\tvalid_0's binary_logloss: 0.681022\n",
      "[84]\tvalid_0's l1: 0.48575\tvalid_0's binary_logloss: 0.68106\n",
      "[85]\tvalid_0's l1: 0.485793\tvalid_0's binary_logloss: 0.681347\n",
      "[86]\tvalid_0's l1: 0.485762\tvalid_0's binary_logloss: 0.681429\n",
      "[87]\tvalid_0's l1: 0.485713\tvalid_0's binary_logloss: 0.681602\n",
      "[88]\tvalid_0's l1: 0.485548\tvalid_0's binary_logloss: 0.681403\n",
      "Early stopping, best iteration is:\n",
      "[83]\tvalid_0's l1: 0.485883\tvalid_0's binary_logloss: 0.681022\n",
      "[1]\tvalid_0's l1: 0.501148\tvalid_0's binary_logloss: 0.696029\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501018\tvalid_0's binary_logloss: 0.695742\n",
      "[3]\tvalid_0's l1: 0.500759\tvalid_0's binary_logloss: 0.695198\n",
      "[4]\tvalid_0's l1: 0.500583\tvalid_0's binary_logloss: 0.694829\n",
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      "[6]\tvalid_0's l1: 0.500154\tvalid_0's binary_logloss: 0.693954\n",
      "[7]\tvalid_0's l1: 0.499921\tvalid_0's binary_logloss: 0.693482\n",
      "[8]\tvalid_0's l1: 0.4997\tvalid_0's binary_logloss: 0.693048\n",
      "[9]\tvalid_0's l1: 0.49953\tvalid_0's binary_logloss: 0.692711\n",
      "[10]\tvalid_0's l1: 0.499335\tvalid_0's binary_logloss: 0.692334\n",
      "[11]\tvalid_0's l1: 0.499264\tvalid_0's binary_logloss: 0.692194\n",
      "[12]\tvalid_0's l1: 0.499051\tvalid_0's binary_logloss: 0.691787\n",
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      "[25]\tvalid_0's l1: 0.496911\tvalid_0's binary_logloss: 0.687784\n",
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      "[28]\tvalid_0's l1: 0.496301\tvalid_0's binary_logloss: 0.686705\n",
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      "[38]\tvalid_0's l1: 0.494627\tvalid_0's binary_logloss: 0.683897\n",
      "[39]\tvalid_0's l1: 0.49448\tvalid_0's binary_logloss: 0.683696\n",
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      "[41]\tvalid_0's l1: 0.494175\tvalid_0's binary_logloss: 0.683266\n",
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      "[48]\tvalid_0's l1: 0.493021\tvalid_0's binary_logloss: 0.681727\n",
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      "[51]\tvalid_0's l1: 0.492738\tvalid_0's binary_logloss: 0.681328\n",
      "[52]\tvalid_0's l1: 0.492632\tvalid_0's binary_logloss: 0.681128\n",
      "[53]\tvalid_0's l1: 0.492481\tvalid_0's binary_logloss: 0.681016\n",
      "[54]\tvalid_0's l1: 0.492395\tvalid_0's binary_logloss: 0.680909\n",
      "[55]\tvalid_0's l1: 0.492225\tvalid_0's binary_logloss: 0.680777\n",
      "[56]\tvalid_0's l1: 0.491968\tvalid_0's binary_logloss: 0.680371\n",
      "[57]\tvalid_0's l1: 0.491882\tvalid_0's binary_logloss: 0.680248\n",
      "[58]\tvalid_0's l1: 0.491774\tvalid_0's binary_logloss: 0.680215\n",
      "[59]\tvalid_0's l1: 0.491728\tvalid_0's binary_logloss: 0.680165\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[60]\tvalid_0's l1: 0.491645\tvalid_0's binary_logloss: 0.68005\n",
      "[61]\tvalid_0's l1: 0.49148\tvalid_0's binary_logloss: 0.679952\n",
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      "[75]\tvalid_0's l1: 0.490086\tvalid_0's binary_logloss: 0.6787\n",
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      "[77]\tvalid_0's l1: 0.48994\tvalid_0's binary_logloss: 0.678704\n",
      "[78]\tvalid_0's l1: 0.48985\tvalid_0's binary_logloss: 0.678745\n",
      "[79]\tvalid_0's l1: 0.489719\tvalid_0's binary_logloss: 0.678536\n",
      "[80]\tvalid_0's l1: 0.489581\tvalid_0's binary_logloss: 0.678555\n",
      "[81]\tvalid_0's l1: 0.489512\tvalid_0's binary_logloss: 0.678442\n",
      "[82]\tvalid_0's l1: 0.489478\tvalid_0's binary_logloss: 0.678418\n",
      "[83]\tvalid_0's l1: 0.48939\tvalid_0's binary_logloss: 0.678477\n",
      "[84]\tvalid_0's l1: 0.489398\tvalid_0's binary_logloss: 0.67858\n",
      "[85]\tvalid_0's l1: 0.489264\tvalid_0's binary_logloss: 0.678621\n",
      "[86]\tvalid_0's l1: 0.4891\tvalid_0's binary_logloss: 0.678342\n",
      "[87]\tvalid_0's l1: 0.488987\tvalid_0's binary_logloss: 0.678441\n",
      "[88]\tvalid_0's l1: 0.488952\tvalid_0's binary_logloss: 0.67842\n",
      "[89]\tvalid_0's l1: 0.488868\tvalid_0's binary_logloss: 0.678507\n",
      "[90]\tvalid_0's l1: 0.488706\tvalid_0's binary_logloss: 0.678235\n",
      "[91]\tvalid_0's l1: 0.488633\tvalid_0's binary_logloss: 0.678311\n",
      "[92]\tvalid_0's l1: 0.488572\tvalid_0's binary_logloss: 0.678208\n",
      "[93]\tvalid_0's l1: 0.488538\tvalid_0's binary_logloss: 0.678192\n",
      "[94]\tvalid_0's l1: 0.488478\tvalid_0's binary_logloss: 0.678366\n",
      "[95]\tvalid_0's l1: 0.488408\tvalid_0's binary_logloss: 0.678459\n",
      "[96]\tvalid_0's l1: 0.488365\tvalid_0's binary_logloss: 0.678426\n",
      "[97]\tvalid_0's l1: 0.488326\tvalid_0's binary_logloss: 0.678418\n",
      "[98]\tvalid_0's l1: 0.488265\tvalid_0's binary_logloss: 0.678637\n",
      "Early stopping, best iteration is:\n",
      "[93]\tvalid_0's l1: 0.488538\tvalid_0's binary_logloss: 0.678192\n",
      "[1]\tvalid_0's l1: 0.501167\tvalid_0's binary_logloss: 0.69602\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501005\tvalid_0's binary_logloss: 0.695667\n",
      "[3]\tvalid_0's l1: 0.500881\tvalid_0's binary_logloss: 0.6954\n",
      "[4]\tvalid_0's l1: 0.500739\tvalid_0's binary_logloss: 0.695106\n",
      "[5]\tvalid_0's l1: 0.500741\tvalid_0's binary_logloss: 0.695112\n",
      "[6]\tvalid_0's l1: 0.500663\tvalid_0's binary_logloss: 0.694968\n",
      "[7]\tvalid_0's l1: 0.500524\tvalid_0's binary_logloss: 0.694701\n",
      "[8]\tvalid_0's l1: 0.500595\tvalid_0's binary_logloss: 0.694829\n",
      "[9]\tvalid_0's l1: 0.500457\tvalid_0's binary_logloss: 0.694579\n",
      "[10]\tvalid_0's l1: 0.500527\tvalid_0's binary_logloss: 0.694722\n",
      "[11]\tvalid_0's l1: 0.500597\tvalid_0's binary_logloss: 0.69488\n",
      "[12]\tvalid_0's l1: 0.500596\tvalid_0's binary_logloss: 0.69489\n",
      "[13]\tvalid_0's l1: 0.500604\tvalid_0's binary_logloss: 0.694917\n",
      "[14]\tvalid_0's l1: 0.500528\tvalid_0's binary_logloss: 0.694815\n",
      "Early stopping, best iteration is:\n",
      "[9]\tvalid_0's l1: 0.500457\tvalid_0's binary_logloss: 0.694579\n",
      "[1]\tvalid_0's l1: 0.501\tvalid_0's binary_logloss: 0.69567\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500713\tvalid_0's binary_logloss: 0.695054\n",
      "[3]\tvalid_0's l1: 0.500464\tvalid_0's binary_logloss: 0.694519\n",
      "[4]\tvalid_0's l1: 0.500188\tvalid_0's binary_logloss: 0.693957\n",
      "[5]\tvalid_0's l1: 0.499944\tvalid_0's binary_logloss: 0.693465\n",
      "[6]\tvalid_0's l1: 0.499667\tvalid_0's binary_logloss: 0.692926\n",
      "[7]\tvalid_0's l1: 0.49937\tvalid_0's binary_logloss: 0.69236\n",
      "[8]\tvalid_0's l1: 0.499134\tvalid_0's binary_logloss: 0.691952\n",
      "[9]\tvalid_0's l1: 0.498876\tvalid_0's binary_logloss: 0.691491\n",
      "[10]\tvalid_0's l1: 0.498836\tvalid_0's binary_logloss: 0.691477\n",
      "[11]\tvalid_0's l1: 0.498797\tvalid_0's binary_logloss: 0.691473\n",
      "[12]\tvalid_0's l1: 0.498558\tvalid_0's binary_logloss: 0.691095\n",
      "[13]\tvalid_0's l1: 0.498519\tvalid_0's binary_logloss: 0.691106\n",
      "[14]\tvalid_0's l1: 0.498529\tvalid_0's binary_logloss: 0.691213\n",
      "[15]\tvalid_0's l1: 0.498514\tvalid_0's binary_logloss: 0.691266\n",
      "[16]\tvalid_0's l1: 0.498477\tvalid_0's binary_logloss: 0.6913\n",
      "[17]\tvalid_0's l1: 0.498462\tvalid_0's binary_logloss: 0.691367\n",
      "Early stopping, best iteration is:\n",
      "[12]\tvalid_0's l1: 0.498558\tvalid_0's binary_logloss: 0.691095\n",
      "[1]\tvalid_0's l1: 0.501151\tvalid_0's binary_logloss: 0.695996\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501011\tvalid_0's binary_logloss: 0.695693\n",
      "[3]\tvalid_0's l1: 0.500896\tvalid_0's binary_logloss: 0.695471\n",
      "[4]\tvalid_0's l1: 0.500764\tvalid_0's binary_logloss: 0.695216\n",
      "[5]\tvalid_0's l1: 0.500666\tvalid_0's binary_logloss: 0.695011\n",
      "[6]\tvalid_0's l1: 0.500574\tvalid_0's binary_logloss: 0.694842\n",
      "[7]\tvalid_0's l1: 0.500439\tvalid_0's binary_logloss: 0.694615\n",
      "[8]\tvalid_0's l1: 0.500349\tvalid_0's binary_logloss: 0.69448\n",
      "[9]\tvalid_0's l1: 0.500216\tvalid_0's binary_logloss: 0.694282\n",
      "[10]\tvalid_0's l1: 0.500128\tvalid_0's binary_logloss: 0.694178\n",
      "[11]\tvalid_0's l1: 0.499997\tvalid_0's binary_logloss: 0.694003\n",
      "[12]\tvalid_0's l1: 0.499743\tvalid_0's binary_logloss: 0.693574\n",
      "[13]\tvalid_0's l1: 0.499709\tvalid_0's binary_logloss: 0.693613\n",
      "[14]\tvalid_0's l1: 0.499633\tvalid_0's binary_logloss: 0.693562\n",
      "[15]\tvalid_0's l1: 0.499333\tvalid_0's binary_logloss: 0.693069\n",
      "[16]\tvalid_0's l1: 0.499208\tvalid_0's binary_logloss: 0.692945\n",
      "[17]\tvalid_0's l1: 0.49894\tvalid_0's binary_logloss: 0.692533\n",
      "[18]\tvalid_0's l1: 0.49882\tvalid_0's binary_logloss: 0.692449\n",
      "[19]\tvalid_0's l1: 0.498762\tvalid_0's binary_logloss: 0.692352\n",
      "[20]\tvalid_0's l1: 0.498711\tvalid_0's binary_logloss: 0.692386\n",
      "[21]\tvalid_0's l1: 0.498511\tvalid_0's binary_logloss: 0.692153\n",
      "[22]\tvalid_0's l1: 0.498434\tvalid_0's binary_logloss: 0.692038\n",
      "[23]\tvalid_0's l1: 0.498177\tvalid_0's binary_logloss: 0.691715\n",
      "[24]\tvalid_0's l1: 0.49812\tvalid_0's binary_logloss: 0.691655\n",
      "[25]\tvalid_0's l1: 0.498046\tvalid_0's binary_logloss: 0.691571\n",
      "[26]\tvalid_0's l1: 0.497846\tvalid_0's binary_logloss: 0.691384\n",
      "[27]\tvalid_0's l1: 0.497775\tvalid_0's binary_logloss: 0.691314\n",
      "[28]\tvalid_0's l1: 0.497474\tvalid_0's binary_logloss: 0.69092\n",
      "[29]\tvalid_0's l1: 0.497386\tvalid_0's binary_logloss: 0.690832\n",
      "[30]\tvalid_0's l1: 0.497191\tvalid_0's binary_logloss: 0.690685\n",
      "[31]\tvalid_0's l1: 0.497005\tvalid_0's binary_logloss: 0.690439\n",
      "[32]\tvalid_0's l1: 0.496917\tvalid_0's binary_logloss: 0.690368\n",
      "[33]\tvalid_0's l1: 0.496802\tvalid_0's binary_logloss: 0.690372\n",
      "[34]\tvalid_0's l1: 0.496623\tvalid_0's binary_logloss: 0.690177\n",
      "[35]\tvalid_0's l1: 0.496428\tvalid_0's binary_logloss: 0.690062\n",
      "[36]\tvalid_0's l1: 0.496326\tvalid_0's binary_logloss: 0.689969\n",
      "[37]\tvalid_0's l1: 0.496215\tvalid_0's binary_logloss: 0.689999\n",
      "[38]\tvalid_0's l1: 0.496157\tvalid_0's binary_logloss: 0.690096\n",
      "[39]\tvalid_0's l1: 0.496077\tvalid_0's binary_logloss: 0.690131\n",
      "[40]\tvalid_0's l1: 0.495973\tvalid_0's binary_logloss: 0.690172\n",
      "[41]\tvalid_0's l1: 0.495873\tvalid_0's binary_logloss: 0.690099\n",
      "Early stopping, best iteration is:\n",
      "[36]\tvalid_0's l1: 0.496326\tvalid_0's binary_logloss: 0.689969\n",
      "[1]\tvalid_0's l1: 0.501038\tvalid_0's binary_logloss: 0.695867\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500707\tvalid_0's binary_logloss: 0.695249\n",
      "[3]\tvalid_0's l1: 0.50038\tvalid_0's binary_logloss: 0.694654\n",
      "[4]\tvalid_0's l1: 0.500074\tvalid_0's binary_logloss: 0.694127\n",
      "[5]\tvalid_0's l1: 0.499753\tvalid_0's binary_logloss: 0.693579\n",
      "[6]\tvalid_0's l1: 0.49947\tvalid_0's binary_logloss: 0.693134\n",
      "[7]\tvalid_0's l1: 0.499172\tvalid_0's binary_logloss: 0.692678\n",
      "[8]\tvalid_0's l1: 0.498909\tvalid_0's binary_logloss: 0.692287\n",
      "[9]\tvalid_0's l1: 0.498618\tvalid_0's binary_logloss: 0.691857\n",
      "[10]\tvalid_0's l1: 0.498334\tvalid_0's binary_logloss: 0.69147\n",
      "[11]\tvalid_0's l1: 0.498024\tvalid_0's binary_logloss: 0.691048\n",
      "[12]\tvalid_0's l1: 0.497763\tvalid_0's binary_logloss: 0.690704\n",
      "[13]\tvalid_0's l1: 0.497441\tvalid_0's binary_logloss: 0.690285\n",
      "[14]\tvalid_0's l1: 0.497088\tvalid_0's binary_logloss: 0.6898\n",
      "[15]\tvalid_0's l1: 0.496962\tvalid_0's binary_logloss: 0.689592\n",
      "[16]\tvalid_0's l1: 0.496837\tvalid_0's binary_logloss: 0.689402\n",
      "[17]\tvalid_0's l1: 0.49667\tvalid_0's binary_logloss: 0.689255\n",
      "[18]\tvalid_0's l1: 0.496527\tvalid_0's binary_logloss: 0.689019\n",
      "[19]\tvalid_0's l1: 0.496326\tvalid_0's binary_logloss: 0.68884\n",
      "[20]\tvalid_0's l1: 0.496205\tvalid_0's binary_logloss: 0.688691\n",
      "[21]\tvalid_0's l1: 0.496086\tvalid_0's binary_logloss: 0.688559\n",
      "[22]\tvalid_0's l1: 0.495855\tvalid_0's binary_logloss: 0.688319\n",
      "[23]\tvalid_0's l1: 0.495747\tvalid_0's binary_logloss: 0.688238\n",
      "[24]\tvalid_0's l1: 0.495544\tvalid_0's binary_logloss: 0.688043\n",
      "[25]\tvalid_0's l1: 0.495454\tvalid_0's binary_logloss: 0.687998\n",
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      "[27]\tvalid_0's l1: 0.495147\tvalid_0's binary_logloss: 0.687556\n",
      "[28]\tvalid_0's l1: 0.494975\tvalid_0's binary_logloss: 0.687278\n",
      "[29]\tvalid_0's l1: 0.494714\tvalid_0's binary_logloss: 0.686849\n",
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      "[31]\tvalid_0's l1: 0.494486\tvalid_0's binary_logloss: 0.686817\n",
      "[32]\tvalid_0's l1: 0.494374\tvalid_0's binary_logloss: 0.686762\n",
      "[33]\tvalid_0's l1: 0.494207\tvalid_0's binary_logloss: 0.686518\n",
      "[34]\tvalid_0's l1: 0.494042\tvalid_0's binary_logloss: 0.686287\n",
      "[35]\tvalid_0's l1: 0.493944\tvalid_0's binary_logloss: 0.686254\n",
      "[36]\tvalid_0's l1: 0.493781\tvalid_0's binary_logloss: 0.686039\n",
      "[37]\tvalid_0's l1: 0.493683\tvalid_0's binary_logloss: 0.686053\n",
      "[38]\tvalid_0's l1: 0.493547\tvalid_0's binary_logloss: 0.68606\n",
      "[39]\tvalid_0's l1: 0.49344\tvalid_0's binary_logloss: 0.686041\n",
      "[40]\tvalid_0's l1: 0.493287\tvalid_0's binary_logloss: 0.685873\n",
      "[41]\tvalid_0's l1: 0.493129\tvalid_0's binary_logloss: 0.685689\n",
      "[42]\tvalid_0's l1: 0.493049\tvalid_0's binary_logloss: 0.685751\n",
      "[43]\tvalid_0's l1: 0.492794\tvalid_0's binary_logloss: 0.685442\n",
      "[44]\tvalid_0's l1: 0.492687\tvalid_0's binary_logloss: 0.685416\n",
      "[45]\tvalid_0's l1: 0.492525\tvalid_0's binary_logloss: 0.685228\n",
      "[46]\tvalid_0's l1: 0.492288\tvalid_0's binary_logloss: 0.684912\n",
      "[47]\tvalid_0's l1: 0.492135\tvalid_0's binary_logloss: 0.684837\n",
      "[48]\tvalid_0's l1: 0.491868\tvalid_0's binary_logloss: 0.684461\n",
      "[49]\tvalid_0's l1: 0.491739\tvalid_0's binary_logloss: 0.6845\n",
      "[50]\tvalid_0's l1: 0.491601\tvalid_0's binary_logloss: 0.684476\n",
      "[51]\tvalid_0's l1: 0.49132\tvalid_0's binary_logloss: 0.684125\n",
      "[52]\tvalid_0's l1: 0.491049\tvalid_0's binary_logloss: 0.683799\n",
      "[53]\tvalid_0's l1: 0.490913\tvalid_0's binary_logloss: 0.683792\n",
      "[54]\tvalid_0's l1: 0.490654\tvalid_0's binary_logloss: 0.683454\n",
      "[55]\tvalid_0's l1: 0.490533\tvalid_0's binary_logloss: 0.683525\n",
      "[56]\tvalid_0's l1: 0.4904\tvalid_0's binary_logloss: 0.683533\n",
      "[57]\tvalid_0's l1: 0.490115\tvalid_0's binary_logloss: 0.683203\n",
      "[58]\tvalid_0's l1: 0.489855\tvalid_0's binary_logloss: 0.682936\n",
      "[59]\tvalid_0's l1: 0.489738\tvalid_0's binary_logloss: 0.683029\n",
      "[60]\tvalid_0's l1: 0.489608\tvalid_0's binary_logloss: 0.683055\n",
      "[61]\tvalid_0's l1: 0.489349\tvalid_0's binary_logloss: 0.682799\n",
      "[62]\tvalid_0's l1: 0.489014\tvalid_0's binary_logloss: 0.682413\n",
      "[63]\tvalid_0's l1: 0.4889\tvalid_0's binary_logloss: 0.682375\n",
      "[64]\tvalid_0's l1: 0.488804\tvalid_0's binary_logloss: 0.682455\n",
      "[65]\tvalid_0's l1: 0.488469\tvalid_0's binary_logloss: 0.682062\n",
      "[66]\tvalid_0's l1: 0.488327\tvalid_0's binary_logloss: 0.681987\n",
      "[67]\tvalid_0's l1: 0.488279\tvalid_0's binary_logloss: 0.682109\n",
      "[68]\tvalid_0's l1: 0.487967\tvalid_0's binary_logloss: 0.681775\n",
      "[69]\tvalid_0's l1: 0.487892\tvalid_0's binary_logloss: 0.681866\n",
      "[70]\tvalid_0's l1: 0.487755\tvalid_0's binary_logloss: 0.681815\n",
      "[71]\tvalid_0's l1: 0.487754\tvalid_0's binary_logloss: 0.682011\n",
      "[72]\tvalid_0's l1: 0.487562\tvalid_0's binary_logloss: 0.681882\n",
      "[73]\tvalid_0's l1: 0.487358\tvalid_0's binary_logloss: 0.681773\n",
      "[74]\tvalid_0's l1: 0.487137\tvalid_0's binary_logloss: 0.681544\n",
      "[75]\tvalid_0's l1: 0.487137\tvalid_0's binary_logloss: 0.681748\n",
      "[76]\tvalid_0's l1: 0.486949\tvalid_0's binary_logloss: 0.681641\n",
      "[77]\tvalid_0's l1: 0.486759\tvalid_0's binary_logloss: 0.681563\n",
      "[78]\tvalid_0's l1: 0.486587\tvalid_0's binary_logloss: 0.681461\n",
      "[79]\tvalid_0's l1: 0.48643\tvalid_0's binary_logloss: 0.68142\n",
      "[80]\tvalid_0's l1: 0.486259\tvalid_0's binary_logloss: 0.681207\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[81]\tvalid_0's l1: 0.486105\tvalid_0's binary_logloss: 0.681183\n",
      "[82]\tvalid_0's l1: 0.486051\tvalid_0's binary_logloss: 0.681228\n",
      "[83]\tvalid_0's l1: 0.485883\tvalid_0's binary_logloss: 0.681022\n",
      "[84]\tvalid_0's l1: 0.48575\tvalid_0's binary_logloss: 0.68106\n",
      "[85]\tvalid_0's l1: 0.485793\tvalid_0's binary_logloss: 0.681347\n",
      "[86]\tvalid_0's l1: 0.485762\tvalid_0's binary_logloss: 0.681429\n",
      "[87]\tvalid_0's l1: 0.485713\tvalid_0's binary_logloss: 0.681602\n",
      "[88]\tvalid_0's l1: 0.485548\tvalid_0's binary_logloss: 0.681403\n",
      "Early stopping, best iteration is:\n",
      "[83]\tvalid_0's l1: 0.485883\tvalid_0's binary_logloss: 0.681022\n",
      "[1]\tvalid_0's l1: 0.501148\tvalid_0's binary_logloss: 0.696029\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501018\tvalid_0's binary_logloss: 0.695742\n",
      "[3]\tvalid_0's l1: 0.500759\tvalid_0's binary_logloss: 0.695198\n",
      "[4]\tvalid_0's l1: 0.500583\tvalid_0's binary_logloss: 0.694829\n",
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      "[6]\tvalid_0's l1: 0.500154\tvalid_0's binary_logloss: 0.693954\n",
      "[7]\tvalid_0's l1: 0.499921\tvalid_0's binary_logloss: 0.693482\n",
      "[8]\tvalid_0's l1: 0.4997\tvalid_0's binary_logloss: 0.693048\n",
      "[9]\tvalid_0's l1: 0.49953\tvalid_0's binary_logloss: 0.692711\n",
      "[10]\tvalid_0's l1: 0.499335\tvalid_0's binary_logloss: 0.692334\n",
      "[11]\tvalid_0's l1: 0.499264\tvalid_0's binary_logloss: 0.692194\n",
      "[12]\tvalid_0's l1: 0.499051\tvalid_0's binary_logloss: 0.691787\n",
      "[13]\tvalid_0's l1: 0.498787\tvalid_0's binary_logloss: 0.691245\n",
      "[14]\tvalid_0's l1: 0.498622\tvalid_0's binary_logloss: 0.690931\n",
      "[15]\tvalid_0's l1: 0.498431\tvalid_0's binary_logloss: 0.690585\n",
      "[16]\tvalid_0's l1: 0.498356\tvalid_0's binary_logloss: 0.690421\n",
      "[17]\tvalid_0's l1: 0.498097\tvalid_0's binary_logloss: 0.689925\n",
      "[18]\tvalid_0's l1: 0.497834\tvalid_0's binary_logloss: 0.689402\n",
      "[19]\tvalid_0's l1: 0.497761\tvalid_0's binary_logloss: 0.689275\n",
      "[20]\tvalid_0's l1: 0.497534\tvalid_0's binary_logloss: 0.688864\n",
      "[21]\tvalid_0's l1: 0.497462\tvalid_0's binary_logloss: 0.688746\n",
      "[22]\tvalid_0's l1: 0.497391\tvalid_0's binary_logloss: 0.688613\n",
      "[23]\tvalid_0's l1: 0.497175\tvalid_0's binary_logloss: 0.688218\n",
      "[24]\tvalid_0's l1: 0.497106\tvalid_0's binary_logloss: 0.688113\n",
      "[25]\tvalid_0's l1: 0.496911\tvalid_0's binary_logloss: 0.687784\n",
      "[26]\tvalid_0's l1: 0.496695\tvalid_0's binary_logloss: 0.687374\n",
      "[27]\tvalid_0's l1: 0.496503\tvalid_0's binary_logloss: 0.687046\n",
      "[28]\tvalid_0's l1: 0.496301\tvalid_0's binary_logloss: 0.686705\n",
      "[29]\tvalid_0's l1: 0.496086\tvalid_0's binary_logloss: 0.686307\n",
      "[30]\tvalid_0's l1: 0.4959\tvalid_0's binary_logloss: 0.686001\n",
      "[31]\tvalid_0's l1: 0.495839\tvalid_0's binary_logloss: 0.685909\n",
      "[32]\tvalid_0's l1: 0.495622\tvalid_0's binary_logloss: 0.68555\n",
      "[33]\tvalid_0's l1: 0.495447\tvalid_0's binary_logloss: 0.685234\n",
      "[34]\tvalid_0's l1: 0.495214\tvalid_0's binary_logloss: 0.684832\n",
      "[35]\tvalid_0's l1: 0.49505\tvalid_0's binary_logloss: 0.68456\n",
      "[36]\tvalid_0's l1: 0.494872\tvalid_0's binary_logloss: 0.684259\n",
      "[37]\tvalid_0's l1: 0.494796\tvalid_0's binary_logloss: 0.684155\n",
      "[38]\tvalid_0's l1: 0.494627\tvalid_0's binary_logloss: 0.683897\n",
      "[39]\tvalid_0's l1: 0.49448\tvalid_0's binary_logloss: 0.683696\n",
      "[40]\tvalid_0's l1: 0.49436\tvalid_0's binary_logloss: 0.683506\n",
      "[41]\tvalid_0's l1: 0.494175\tvalid_0's binary_logloss: 0.683266\n",
      "[42]\tvalid_0's l1: 0.49398\tvalid_0's binary_logloss: 0.682937\n",
      "[43]\tvalid_0's l1: 0.493788\tvalid_0's binary_logloss: 0.682627\n",
      "[44]\tvalid_0's l1: 0.493669\tvalid_0's binary_logloss: 0.682511\n",
      "[45]\tvalid_0's l1: 0.493501\tvalid_0's binary_logloss: 0.682285\n",
      "[46]\tvalid_0's l1: 0.493313\tvalid_0's binary_logloss: 0.681986\n",
      "[47]\tvalid_0's l1: 0.493196\tvalid_0's binary_logloss: 0.681895\n",
      "[48]\tvalid_0's l1: 0.493021\tvalid_0's binary_logloss: 0.681727\n",
      "[49]\tvalid_0's l1: 0.492835\tvalid_0's binary_logloss: 0.681439\n",
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      "[52]\tvalid_0's l1: 0.492632\tvalid_0's binary_logloss: 0.681128\n",
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      "[55]\tvalid_0's l1: 0.492225\tvalid_0's binary_logloss: 0.680777\n",
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      "[68]\tvalid_0's l1: 0.490821\tvalid_0's binary_logloss: 0.679316\n",
      "[69]\tvalid_0's l1: 0.490749\tvalid_0's binary_logloss: 0.679203\n",
      "[70]\tvalid_0's l1: 0.490629\tvalid_0's binary_logloss: 0.679181\n",
      "[71]\tvalid_0's l1: 0.490552\tvalid_0's binary_logloss: 0.679083\n",
      "[72]\tvalid_0's l1: 0.490472\tvalid_0's binary_logloss: 0.679104\n",
      "[73]\tvalid_0's l1: 0.490336\tvalid_0's binary_logloss: 0.678884\n",
      "[74]\tvalid_0's l1: 0.490212\tvalid_0's binary_logloss: 0.678899\n",
      "[75]\tvalid_0's l1: 0.490086\tvalid_0's binary_logloss: 0.6787\n",
      "[76]\tvalid_0's l1: 0.489975\tvalid_0's binary_logloss: 0.678733\n",
      "[77]\tvalid_0's l1: 0.48994\tvalid_0's binary_logloss: 0.678704\n",
      "[78]\tvalid_0's l1: 0.48985\tvalid_0's binary_logloss: 0.678745\n",
      "[79]\tvalid_0's l1: 0.489719\tvalid_0's binary_logloss: 0.678536\n",
      "[80]\tvalid_0's l1: 0.489581\tvalid_0's binary_logloss: 0.678555\n",
      "[81]\tvalid_0's l1: 0.489512\tvalid_0's binary_logloss: 0.678442\n",
      "[82]\tvalid_0's l1: 0.489478\tvalid_0's binary_logloss: 0.678418\n",
      "[83]\tvalid_0's l1: 0.48939\tvalid_0's binary_logloss: 0.678477\n",
      "[84]\tvalid_0's l1: 0.489398\tvalid_0's binary_logloss: 0.67858\n",
      "[85]\tvalid_0's l1: 0.489264\tvalid_0's binary_logloss: 0.678621\n",
      "[86]\tvalid_0's l1: 0.4891\tvalid_0's binary_logloss: 0.678342\n",
      "[87]\tvalid_0's l1: 0.488987\tvalid_0's binary_logloss: 0.678441\n",
      "[88]\tvalid_0's l1: 0.488952\tvalid_0's binary_logloss: 0.67842\n",
      "[89]\tvalid_0's l1: 0.488868\tvalid_0's binary_logloss: 0.678507\n",
      "[90]\tvalid_0's l1: 0.488706\tvalid_0's binary_logloss: 0.678235\n",
      "[91]\tvalid_0's l1: 0.488633\tvalid_0's binary_logloss: 0.678311\n",
      "[92]\tvalid_0's l1: 0.488572\tvalid_0's binary_logloss: 0.678208\n",
      "[93]\tvalid_0's l1: 0.488538\tvalid_0's binary_logloss: 0.678192\n",
      "[94]\tvalid_0's l1: 0.488478\tvalid_0's binary_logloss: 0.678366\n",
      "[95]\tvalid_0's l1: 0.488408\tvalid_0's binary_logloss: 0.678459\n",
      "[96]\tvalid_0's l1: 0.488365\tvalid_0's binary_logloss: 0.678426\n",
      "[97]\tvalid_0's l1: 0.488326\tvalid_0's binary_logloss: 0.678418\n",
      "[98]\tvalid_0's l1: 0.488265\tvalid_0's binary_logloss: 0.678637\n",
      "Early stopping, best iteration is:\n",
      "[93]\tvalid_0's l1: 0.488538\tvalid_0's binary_logloss: 0.678192\n",
      "[1]\tvalid_0's l1: 0.501167\tvalid_0's binary_logloss: 0.69602\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501005\tvalid_0's binary_logloss: 0.695667\n",
      "[3]\tvalid_0's l1: 0.500881\tvalid_0's binary_logloss: 0.6954\n",
      "[4]\tvalid_0's l1: 0.500739\tvalid_0's binary_logloss: 0.695106\n",
      "[5]\tvalid_0's l1: 0.500741\tvalid_0's binary_logloss: 0.695112\n",
      "[6]\tvalid_0's l1: 0.500663\tvalid_0's binary_logloss: 0.694968\n",
      "[7]\tvalid_0's l1: 0.500524\tvalid_0's binary_logloss: 0.694701\n",
      "[8]\tvalid_0's l1: 0.500595\tvalid_0's binary_logloss: 0.694829\n",
      "[9]\tvalid_0's l1: 0.500457\tvalid_0's binary_logloss: 0.694579\n",
      "[10]\tvalid_0's l1: 0.500527\tvalid_0's binary_logloss: 0.694722\n",
      "[11]\tvalid_0's l1: 0.500597\tvalid_0's binary_logloss: 0.69488\n",
      "[12]\tvalid_0's l1: 0.500596\tvalid_0's binary_logloss: 0.69489\n",
      "[13]\tvalid_0's l1: 0.500604\tvalid_0's binary_logloss: 0.694917\n",
      "[14]\tvalid_0's l1: 0.500528\tvalid_0's binary_logloss: 0.694815\n",
      "Early stopping, best iteration is:\n",
      "[9]\tvalid_0's l1: 0.500457\tvalid_0's binary_logloss: 0.694579\n",
      "[1]\tvalid_0's l1: 0.501\tvalid_0's binary_logloss: 0.69567\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500713\tvalid_0's binary_logloss: 0.695054\n",
      "[3]\tvalid_0's l1: 0.500464\tvalid_0's binary_logloss: 0.694519\n",
      "[4]\tvalid_0's l1: 0.500188\tvalid_0's binary_logloss: 0.693957\n",
      "[5]\tvalid_0's l1: 0.499944\tvalid_0's binary_logloss: 0.693465\n",
      "[6]\tvalid_0's l1: 0.499667\tvalid_0's binary_logloss: 0.692926\n",
      "[7]\tvalid_0's l1: 0.49937\tvalid_0's binary_logloss: 0.69236\n",
      "[8]\tvalid_0's l1: 0.499134\tvalid_0's binary_logloss: 0.691952\n",
      "[9]\tvalid_0's l1: 0.498876\tvalid_0's binary_logloss: 0.691491\n",
      "[10]\tvalid_0's l1: 0.498836\tvalid_0's binary_logloss: 0.691477\n",
      "[11]\tvalid_0's l1: 0.498797\tvalid_0's binary_logloss: 0.691473\n",
      "[12]\tvalid_0's l1: 0.498558\tvalid_0's binary_logloss: 0.691095\n",
      "[13]\tvalid_0's l1: 0.498519\tvalid_0's binary_logloss: 0.691106\n",
      "[14]\tvalid_0's l1: 0.498529\tvalid_0's binary_logloss: 0.691213\n",
      "[15]\tvalid_0's l1: 0.498514\tvalid_0's binary_logloss: 0.691266\n",
      "[16]\tvalid_0's l1: 0.498477\tvalid_0's binary_logloss: 0.6913\n",
      "[17]\tvalid_0's l1: 0.498462\tvalid_0's binary_logloss: 0.691367\n",
      "Early stopping, best iteration is:\n",
      "[12]\tvalid_0's l1: 0.498558\tvalid_0's binary_logloss: 0.691095\n",
      "[1]\tvalid_0's l1: 0.501151\tvalid_0's binary_logloss: 0.695996\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501011\tvalid_0's binary_logloss: 0.695693\n",
      "[3]\tvalid_0's l1: 0.500896\tvalid_0's binary_logloss: 0.695471\n",
      "[4]\tvalid_0's l1: 0.500764\tvalid_0's binary_logloss: 0.695216\n",
      "[5]\tvalid_0's l1: 0.500666\tvalid_0's binary_logloss: 0.695011\n",
      "[6]\tvalid_0's l1: 0.500574\tvalid_0's binary_logloss: 0.694842\n",
      "[7]\tvalid_0's l1: 0.500439\tvalid_0's binary_logloss: 0.694615\n",
      "[8]\tvalid_0's l1: 0.500349\tvalid_0's binary_logloss: 0.69448\n",
      "[9]\tvalid_0's l1: 0.500216\tvalid_0's binary_logloss: 0.694282\n",
      "[10]\tvalid_0's l1: 0.500128\tvalid_0's binary_logloss: 0.694178\n",
      "[11]\tvalid_0's l1: 0.499997\tvalid_0's binary_logloss: 0.694003\n",
      "[12]\tvalid_0's l1: 0.499743\tvalid_0's binary_logloss: 0.693574\n",
      "[13]\tvalid_0's l1: 0.499709\tvalid_0's binary_logloss: 0.693613\n",
      "[14]\tvalid_0's l1: 0.499633\tvalid_0's binary_logloss: 0.693562\n",
      "[15]\tvalid_0's l1: 0.499333\tvalid_0's binary_logloss: 0.693069\n",
      "[16]\tvalid_0's l1: 0.499208\tvalid_0's binary_logloss: 0.692945\n",
      "[17]\tvalid_0's l1: 0.49894\tvalid_0's binary_logloss: 0.692533\n",
      "[18]\tvalid_0's l1: 0.49882\tvalid_0's binary_logloss: 0.692449\n",
      "[19]\tvalid_0's l1: 0.498762\tvalid_0's binary_logloss: 0.692352\n",
      "[20]\tvalid_0's l1: 0.498711\tvalid_0's binary_logloss: 0.692386\n",
      "[21]\tvalid_0's l1: 0.498511\tvalid_0's binary_logloss: 0.692153\n",
      "[22]\tvalid_0's l1: 0.498434\tvalid_0's binary_logloss: 0.692038\n",
      "[23]\tvalid_0's l1: 0.498177\tvalid_0's binary_logloss: 0.691715\n",
      "[24]\tvalid_0's l1: 0.49812\tvalid_0's binary_logloss: 0.691655\n",
      "[25]\tvalid_0's l1: 0.498046\tvalid_0's binary_logloss: 0.691571\n",
      "[26]\tvalid_0's l1: 0.497846\tvalid_0's binary_logloss: 0.691384\n",
      "[27]\tvalid_0's l1: 0.497775\tvalid_0's binary_logloss: 0.691314\n",
      "[28]\tvalid_0's l1: 0.497474\tvalid_0's binary_logloss: 0.69092\n",
      "[29]\tvalid_0's l1: 0.497386\tvalid_0's binary_logloss: 0.690832\n",
      "[30]\tvalid_0's l1: 0.497191\tvalid_0's binary_logloss: 0.690685\n",
      "[31]\tvalid_0's l1: 0.497005\tvalid_0's binary_logloss: 0.690439\n",
      "[32]\tvalid_0's l1: 0.496917\tvalid_0's binary_logloss: 0.690368\n",
      "[33]\tvalid_0's l1: 0.496802\tvalid_0's binary_logloss: 0.690372\n",
      "[34]\tvalid_0's l1: 0.496623\tvalid_0's binary_logloss: 0.690177\n",
      "[35]\tvalid_0's l1: 0.496428\tvalid_0's binary_logloss: 0.690062\n",
      "[36]\tvalid_0's l1: 0.496326\tvalid_0's binary_logloss: 0.689969\n",
      "[37]\tvalid_0's l1: 0.496215\tvalid_0's binary_logloss: 0.689999\n",
      "[38]\tvalid_0's l1: 0.496157\tvalid_0's binary_logloss: 0.690096\n",
      "[39]\tvalid_0's l1: 0.496077\tvalid_0's binary_logloss: 0.690131\n",
      "[40]\tvalid_0's l1: 0.495973\tvalid_0's binary_logloss: 0.690172\n",
      "[41]\tvalid_0's l1: 0.495873\tvalid_0's binary_logloss: 0.690099\n",
      "Early stopping, best iteration is:\n",
      "[36]\tvalid_0's l1: 0.496326\tvalid_0's binary_logloss: 0.689969\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1]\tvalid_0's l1: 0.501038\tvalid_0's binary_logloss: 0.695867\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500707\tvalid_0's binary_logloss: 0.695249\n",
      "[3]\tvalid_0's l1: 0.50038\tvalid_0's binary_logloss: 0.694654\n",
      "[4]\tvalid_0's l1: 0.500074\tvalid_0's binary_logloss: 0.694127\n",
      "[5]\tvalid_0's l1: 0.499753\tvalid_0's binary_logloss: 0.693579\n",
      "[6]\tvalid_0's l1: 0.49947\tvalid_0's binary_logloss: 0.693134\n",
      "[7]\tvalid_0's l1: 0.499172\tvalid_0's binary_logloss: 0.692678\n",
      "[8]\tvalid_0's l1: 0.498909\tvalid_0's binary_logloss: 0.692287\n",
      "[9]\tvalid_0's l1: 0.498618\tvalid_0's binary_logloss: 0.691857\n",
      "[10]\tvalid_0's l1: 0.498334\tvalid_0's binary_logloss: 0.69147\n",
      "[11]\tvalid_0's l1: 0.498024\tvalid_0's binary_logloss: 0.691048\n",
      "[12]\tvalid_0's l1: 0.497763\tvalid_0's binary_logloss: 0.690704\n",
      "[13]\tvalid_0's l1: 0.497441\tvalid_0's binary_logloss: 0.690285\n",
      "[14]\tvalid_0's l1: 0.497088\tvalid_0's binary_logloss: 0.6898\n",
      "[15]\tvalid_0's l1: 0.496962\tvalid_0's binary_logloss: 0.689592\n",
      "[16]\tvalid_0's l1: 0.496837\tvalid_0's binary_logloss: 0.689402\n",
      "[17]\tvalid_0's l1: 0.49667\tvalid_0's binary_logloss: 0.689255\n",
      "[18]\tvalid_0's l1: 0.496527\tvalid_0's binary_logloss: 0.689019\n",
      "[19]\tvalid_0's l1: 0.496326\tvalid_0's binary_logloss: 0.68884\n",
      "[20]\tvalid_0's l1: 0.496205\tvalid_0's binary_logloss: 0.688691\n",
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      "[23]\tvalid_0's l1: 0.495747\tvalid_0's binary_logloss: 0.688238\n",
      "[24]\tvalid_0's l1: 0.495544\tvalid_0's binary_logloss: 0.688043\n",
      "[25]\tvalid_0's l1: 0.495454\tvalid_0's binary_logloss: 0.687998\n",
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      "[28]\tvalid_0's l1: 0.494975\tvalid_0's binary_logloss: 0.687278\n",
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      "[33]\tvalid_0's l1: 0.494207\tvalid_0's binary_logloss: 0.686518\n",
      "[34]\tvalid_0's l1: 0.494042\tvalid_0's binary_logloss: 0.686287\n",
      "[35]\tvalid_0's l1: 0.493944\tvalid_0's binary_logloss: 0.686254\n",
      "[36]\tvalid_0's l1: 0.493781\tvalid_0's binary_logloss: 0.686039\n",
      "[37]\tvalid_0's l1: 0.493683\tvalid_0's binary_logloss: 0.686053\n",
      "[38]\tvalid_0's l1: 0.493547\tvalid_0's binary_logloss: 0.68606\n",
      "[39]\tvalid_0's l1: 0.49344\tvalid_0's binary_logloss: 0.686041\n",
      "[40]\tvalid_0's l1: 0.493287\tvalid_0's binary_logloss: 0.685873\n",
      "[41]\tvalid_0's l1: 0.493129\tvalid_0's binary_logloss: 0.685689\n",
      "[42]\tvalid_0's l1: 0.493049\tvalid_0's binary_logloss: 0.685751\n",
      "[43]\tvalid_0's l1: 0.492794\tvalid_0's binary_logloss: 0.685442\n",
      "[44]\tvalid_0's l1: 0.492687\tvalid_0's binary_logloss: 0.685416\n",
      "[45]\tvalid_0's l1: 0.492525\tvalid_0's binary_logloss: 0.685228\n",
      "[46]\tvalid_0's l1: 0.492288\tvalid_0's binary_logloss: 0.684912\n",
      "[47]\tvalid_0's l1: 0.492135\tvalid_0's binary_logloss: 0.684837\n",
      "[48]\tvalid_0's l1: 0.491868\tvalid_0's binary_logloss: 0.684461\n",
      "[49]\tvalid_0's l1: 0.491739\tvalid_0's binary_logloss: 0.6845\n",
      "[50]\tvalid_0's l1: 0.491601\tvalid_0's binary_logloss: 0.684476\n",
      "[51]\tvalid_0's l1: 0.49132\tvalid_0's binary_logloss: 0.684125\n",
      "[52]\tvalid_0's l1: 0.491049\tvalid_0's binary_logloss: 0.683799\n",
      "[53]\tvalid_0's l1: 0.490913\tvalid_0's binary_logloss: 0.683792\n",
      "[54]\tvalid_0's l1: 0.490654\tvalid_0's binary_logloss: 0.683454\n",
      "[55]\tvalid_0's l1: 0.490533\tvalid_0's binary_logloss: 0.683525\n",
      "[56]\tvalid_0's l1: 0.4904\tvalid_0's binary_logloss: 0.683533\n",
      "[57]\tvalid_0's l1: 0.490115\tvalid_0's binary_logloss: 0.683203\n",
      "[58]\tvalid_0's l1: 0.489855\tvalid_0's binary_logloss: 0.682936\n",
      "[59]\tvalid_0's l1: 0.489738\tvalid_0's binary_logloss: 0.683029\n",
      "[60]\tvalid_0's l1: 0.489608\tvalid_0's binary_logloss: 0.683055\n",
      "[61]\tvalid_0's l1: 0.489349\tvalid_0's binary_logloss: 0.682799\n",
      "[62]\tvalid_0's l1: 0.489014\tvalid_0's binary_logloss: 0.682413\n",
      "[63]\tvalid_0's l1: 0.4889\tvalid_0's binary_logloss: 0.682375\n",
      "[64]\tvalid_0's l1: 0.488804\tvalid_0's binary_logloss: 0.682455\n",
      "[65]\tvalid_0's l1: 0.488469\tvalid_0's binary_logloss: 0.682062\n",
      "[66]\tvalid_0's l1: 0.488327\tvalid_0's binary_logloss: 0.681987\n",
      "[67]\tvalid_0's l1: 0.488279\tvalid_0's binary_logloss: 0.682109\n",
      "[68]\tvalid_0's l1: 0.487967\tvalid_0's binary_logloss: 0.681775\n",
      "[69]\tvalid_0's l1: 0.487892\tvalid_0's binary_logloss: 0.681866\n",
      "[70]\tvalid_0's l1: 0.487755\tvalid_0's binary_logloss: 0.681815\n",
      "[71]\tvalid_0's l1: 0.487754\tvalid_0's binary_logloss: 0.682011\n",
      "[72]\tvalid_0's l1: 0.487562\tvalid_0's binary_logloss: 0.681882\n",
      "[73]\tvalid_0's l1: 0.487358\tvalid_0's binary_logloss: 0.681773\n",
      "[74]\tvalid_0's l1: 0.487137\tvalid_0's binary_logloss: 0.681544\n",
      "[75]\tvalid_0's l1: 0.487137\tvalid_0's binary_logloss: 0.681748\n",
      "[76]\tvalid_0's l1: 0.486949\tvalid_0's binary_logloss: 0.681641\n",
      "[77]\tvalid_0's l1: 0.486759\tvalid_0's binary_logloss: 0.681563\n",
      "[78]\tvalid_0's l1: 0.486587\tvalid_0's binary_logloss: 0.681461\n",
      "[79]\tvalid_0's l1: 0.48643\tvalid_0's binary_logloss: 0.68142\n",
      "[80]\tvalid_0's l1: 0.486259\tvalid_0's binary_logloss: 0.681207\n",
      "[81]\tvalid_0's l1: 0.486105\tvalid_0's binary_logloss: 0.681183\n",
      "[82]\tvalid_0's l1: 0.486051\tvalid_0's binary_logloss: 0.681228\n",
      "[83]\tvalid_0's l1: 0.485883\tvalid_0's binary_logloss: 0.681022\n",
      "[84]\tvalid_0's l1: 0.48575\tvalid_0's binary_logloss: 0.68106\n",
      "[85]\tvalid_0's l1: 0.485793\tvalid_0's binary_logloss: 0.681347\n",
      "[86]\tvalid_0's l1: 0.485762\tvalid_0's binary_logloss: 0.681429\n",
      "[87]\tvalid_0's l1: 0.485713\tvalid_0's binary_logloss: 0.681602\n",
      "[88]\tvalid_0's l1: 0.485548\tvalid_0's binary_logloss: 0.681403\n",
      "Early stopping, best iteration is:\n",
      "[83]\tvalid_0's l1: 0.485883\tvalid_0's binary_logloss: 0.681022\n",
      "[1]\tvalid_0's l1: 0.501148\tvalid_0's binary_logloss: 0.696029\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501018\tvalid_0's binary_logloss: 0.695742\n",
      "[3]\tvalid_0's l1: 0.500759\tvalid_0's binary_logloss: 0.695198\n",
      "[4]\tvalid_0's l1: 0.500583\tvalid_0's binary_logloss: 0.694829\n",
      "[5]\tvalid_0's l1: 0.500328\tvalid_0's binary_logloss: 0.694308\n",
      "[6]\tvalid_0's l1: 0.500154\tvalid_0's binary_logloss: 0.693954\n",
      "[7]\tvalid_0's l1: 0.499921\tvalid_0's binary_logloss: 0.693482\n",
      "[8]\tvalid_0's l1: 0.4997\tvalid_0's binary_logloss: 0.693048\n",
      "[9]\tvalid_0's l1: 0.49953\tvalid_0's binary_logloss: 0.692711\n",
      "[10]\tvalid_0's l1: 0.499335\tvalid_0's binary_logloss: 0.692334\n",
      "[11]\tvalid_0's l1: 0.499264\tvalid_0's binary_logloss: 0.692194\n",
      "[12]\tvalid_0's l1: 0.499051\tvalid_0's binary_logloss: 0.691787\n",
      "[13]\tvalid_0's l1: 0.498787\tvalid_0's binary_logloss: 0.691245\n",
      "[14]\tvalid_0's l1: 0.498622\tvalid_0's binary_logloss: 0.690931\n",
      "[15]\tvalid_0's l1: 0.498431\tvalid_0's binary_logloss: 0.690585\n",
      "[16]\tvalid_0's l1: 0.498356\tvalid_0's binary_logloss: 0.690421\n",
      "[17]\tvalid_0's l1: 0.498097\tvalid_0's binary_logloss: 0.689925\n",
      "[18]\tvalid_0's l1: 0.497834\tvalid_0's binary_logloss: 0.689402\n",
      "[19]\tvalid_0's l1: 0.497761\tvalid_0's binary_logloss: 0.689275\n",
      "[20]\tvalid_0's l1: 0.497534\tvalid_0's binary_logloss: 0.688864\n",
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      "[22]\tvalid_0's l1: 0.497391\tvalid_0's binary_logloss: 0.688613\n",
      "[23]\tvalid_0's l1: 0.497175\tvalid_0's binary_logloss: 0.688218\n",
      "[24]\tvalid_0's l1: 0.497106\tvalid_0's binary_logloss: 0.688113\n",
      "[25]\tvalid_0's l1: 0.496911\tvalid_0's binary_logloss: 0.687784\n",
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      "[33]\tvalid_0's l1: 0.495447\tvalid_0's binary_logloss: 0.685234\n",
      "[34]\tvalid_0's l1: 0.495214\tvalid_0's binary_logloss: 0.684832\n",
      "[35]\tvalid_0's l1: 0.49505\tvalid_0's binary_logloss: 0.68456\n",
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      "[53]\tvalid_0's l1: 0.492481\tvalid_0's binary_logloss: 0.681016\n",
      "[54]\tvalid_0's l1: 0.492395\tvalid_0's binary_logloss: 0.680909\n",
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      "[63]\tvalid_0's l1: 0.491307\tvalid_0's binary_logloss: 0.67969\n",
      "[64]\tvalid_0's l1: 0.491202\tvalid_0's binary_logloss: 0.67968\n",
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      "[66]\tvalid_0's l1: 0.490989\tvalid_0's binary_logloss: 0.679557\n",
      "[67]\tvalid_0's l1: 0.490959\tvalid_0's binary_logloss: 0.679544\n",
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      "[69]\tvalid_0's l1: 0.490749\tvalid_0's binary_logloss: 0.679203\n",
      "[70]\tvalid_0's l1: 0.490629\tvalid_0's binary_logloss: 0.679181\n",
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      "[73]\tvalid_0's l1: 0.490336\tvalid_0's binary_logloss: 0.678884\n",
      "[74]\tvalid_0's l1: 0.490212\tvalid_0's binary_logloss: 0.678899\n",
      "[75]\tvalid_0's l1: 0.490086\tvalid_0's binary_logloss: 0.6787\n",
      "[76]\tvalid_0's l1: 0.489975\tvalid_0's binary_logloss: 0.678733\n",
      "[77]\tvalid_0's l1: 0.48994\tvalid_0's binary_logloss: 0.678704\n",
      "[78]\tvalid_0's l1: 0.48985\tvalid_0's binary_logloss: 0.678745\n",
      "[79]\tvalid_0's l1: 0.489719\tvalid_0's binary_logloss: 0.678536\n",
      "[80]\tvalid_0's l1: 0.489581\tvalid_0's binary_logloss: 0.678555\n",
      "[81]\tvalid_0's l1: 0.489512\tvalid_0's binary_logloss: 0.678442\n",
      "[82]\tvalid_0's l1: 0.489478\tvalid_0's binary_logloss: 0.678418\n",
      "[83]\tvalid_0's l1: 0.48939\tvalid_0's binary_logloss: 0.678477\n",
      "[84]\tvalid_0's l1: 0.489398\tvalid_0's binary_logloss: 0.67858\n",
      "[85]\tvalid_0's l1: 0.489264\tvalid_0's binary_logloss: 0.678621\n",
      "[86]\tvalid_0's l1: 0.4891\tvalid_0's binary_logloss: 0.678342\n",
      "[87]\tvalid_0's l1: 0.488987\tvalid_0's binary_logloss: 0.678441\n",
      "[88]\tvalid_0's l1: 0.488952\tvalid_0's binary_logloss: 0.67842\n",
      "[89]\tvalid_0's l1: 0.488868\tvalid_0's binary_logloss: 0.678507\n",
      "[90]\tvalid_0's l1: 0.488706\tvalid_0's binary_logloss: 0.678235\n",
      "[91]\tvalid_0's l1: 0.488633\tvalid_0's binary_logloss: 0.678311\n",
      "[92]\tvalid_0's l1: 0.488572\tvalid_0's binary_logloss: 0.678208\n",
      "[93]\tvalid_0's l1: 0.488538\tvalid_0's binary_logloss: 0.678192\n",
      "[94]\tvalid_0's l1: 0.488478\tvalid_0's binary_logloss: 0.678366\n",
      "[95]\tvalid_0's l1: 0.488408\tvalid_0's binary_logloss: 0.678459\n",
      "[96]\tvalid_0's l1: 0.488365\tvalid_0's binary_logloss: 0.678426\n",
      "[97]\tvalid_0's l1: 0.488326\tvalid_0's binary_logloss: 0.678418\n",
      "[98]\tvalid_0's l1: 0.488265\tvalid_0's binary_logloss: 0.678637\n",
      "Early stopping, best iteration is:\n",
      "[93]\tvalid_0's l1: 0.488538\tvalid_0's binary_logloss: 0.678192\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1]\tvalid_0's l1: 0.501167\tvalid_0's binary_logloss: 0.69602\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501005\tvalid_0's binary_logloss: 0.695667\n",
      "[3]\tvalid_0's l1: 0.500881\tvalid_0's binary_logloss: 0.6954\n",
      "[4]\tvalid_0's l1: 0.500739\tvalid_0's binary_logloss: 0.695106\n",
      "[5]\tvalid_0's l1: 0.500741\tvalid_0's binary_logloss: 0.695112\n",
      "[6]\tvalid_0's l1: 0.500663\tvalid_0's binary_logloss: 0.694968\n",
      "[7]\tvalid_0's l1: 0.500524\tvalid_0's binary_logloss: 0.694701\n",
      "[8]\tvalid_0's l1: 0.500595\tvalid_0's binary_logloss: 0.694829\n",
      "[9]\tvalid_0's l1: 0.500457\tvalid_0's binary_logloss: 0.694579\n",
      "[10]\tvalid_0's l1: 0.500527\tvalid_0's binary_logloss: 0.694722\n",
      "[11]\tvalid_0's l1: 0.500597\tvalid_0's binary_logloss: 0.69488\n",
      "[12]\tvalid_0's l1: 0.500596\tvalid_0's binary_logloss: 0.69489\n",
      "[13]\tvalid_0's l1: 0.500604\tvalid_0's binary_logloss: 0.694917\n",
      "[14]\tvalid_0's l1: 0.500528\tvalid_0's binary_logloss: 0.694815\n",
      "Early stopping, best iteration is:\n",
      "[9]\tvalid_0's l1: 0.500457\tvalid_0's binary_logloss: 0.694579\n",
      "[1]\tvalid_0's l1: 0.501\tvalid_0's binary_logloss: 0.69567\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500713\tvalid_0's binary_logloss: 0.695054\n",
      "[3]\tvalid_0's l1: 0.500464\tvalid_0's binary_logloss: 0.694519\n",
      "[4]\tvalid_0's l1: 0.500188\tvalid_0's binary_logloss: 0.693957\n",
      "[5]\tvalid_0's l1: 0.499944\tvalid_0's binary_logloss: 0.693465\n",
      "[6]\tvalid_0's l1: 0.499667\tvalid_0's binary_logloss: 0.692926\n",
      "[7]\tvalid_0's l1: 0.49937\tvalid_0's binary_logloss: 0.69236\n",
      "[8]\tvalid_0's l1: 0.499134\tvalid_0's binary_logloss: 0.691952\n",
      "[9]\tvalid_0's l1: 0.498876\tvalid_0's binary_logloss: 0.691491\n",
      "[10]\tvalid_0's l1: 0.498836\tvalid_0's binary_logloss: 0.691477\n",
      "[11]\tvalid_0's l1: 0.498797\tvalid_0's binary_logloss: 0.691473\n",
      "[12]\tvalid_0's l1: 0.498558\tvalid_0's binary_logloss: 0.691095\n",
      "[13]\tvalid_0's l1: 0.498519\tvalid_0's binary_logloss: 0.691106\n",
      "[14]\tvalid_0's l1: 0.498529\tvalid_0's binary_logloss: 0.691213\n",
      "[15]\tvalid_0's l1: 0.498514\tvalid_0's binary_logloss: 0.691266\n",
      "[16]\tvalid_0's l1: 0.498477\tvalid_0's binary_logloss: 0.6913\n",
      "[17]\tvalid_0's l1: 0.498462\tvalid_0's binary_logloss: 0.691367\n",
      "Early stopping, best iteration is:\n",
      "[12]\tvalid_0's l1: 0.498558\tvalid_0's binary_logloss: 0.691095\n",
      "[1]\tvalid_0's l1: 0.501151\tvalid_0's binary_logloss: 0.695996\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501011\tvalid_0's binary_logloss: 0.695693\n",
      "[3]\tvalid_0's l1: 0.500896\tvalid_0's binary_logloss: 0.695471\n",
      "[4]\tvalid_0's l1: 0.500764\tvalid_0's binary_logloss: 0.695216\n",
      "[5]\tvalid_0's l1: 0.500666\tvalid_0's binary_logloss: 0.695011\n",
      "[6]\tvalid_0's l1: 0.500574\tvalid_0's binary_logloss: 0.694842\n",
      "[7]\tvalid_0's l1: 0.500439\tvalid_0's binary_logloss: 0.694615\n",
      "[8]\tvalid_0's l1: 0.500349\tvalid_0's binary_logloss: 0.69448\n",
      "[9]\tvalid_0's l1: 0.500216\tvalid_0's binary_logloss: 0.694282\n",
      "[10]\tvalid_0's l1: 0.500128\tvalid_0's binary_logloss: 0.694178\n",
      "[11]\tvalid_0's l1: 0.499997\tvalid_0's binary_logloss: 0.694003\n",
      "[12]\tvalid_0's l1: 0.499743\tvalid_0's binary_logloss: 0.693574\n",
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      "[16]\tvalid_0's l1: 0.499208\tvalid_0's binary_logloss: 0.692945\n",
      "[17]\tvalid_0's l1: 0.49894\tvalid_0's binary_logloss: 0.692533\n",
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      "[20]\tvalid_0's l1: 0.498711\tvalid_0's binary_logloss: 0.692386\n",
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      "[23]\tvalid_0's l1: 0.498177\tvalid_0's binary_logloss: 0.691715\n",
      "[24]\tvalid_0's l1: 0.49812\tvalid_0's binary_logloss: 0.691655\n",
      "[25]\tvalid_0's l1: 0.498046\tvalid_0's binary_logloss: 0.691571\n",
      "[26]\tvalid_0's l1: 0.497846\tvalid_0's binary_logloss: 0.691384\n",
      "[27]\tvalid_0's l1: 0.497775\tvalid_0's binary_logloss: 0.691314\n",
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      "[29]\tvalid_0's l1: 0.497386\tvalid_0's binary_logloss: 0.690832\n",
      "[30]\tvalid_0's l1: 0.497191\tvalid_0's binary_logloss: 0.690685\n",
      "[31]\tvalid_0's l1: 0.497005\tvalid_0's binary_logloss: 0.690439\n",
      "[32]\tvalid_0's l1: 0.496917\tvalid_0's binary_logloss: 0.690368\n",
      "[33]\tvalid_0's l1: 0.496802\tvalid_0's binary_logloss: 0.690372\n",
      "[34]\tvalid_0's l1: 0.496623\tvalid_0's binary_logloss: 0.690177\n",
      "[35]\tvalid_0's l1: 0.496428\tvalid_0's binary_logloss: 0.690062\n",
      "[36]\tvalid_0's l1: 0.496326\tvalid_0's binary_logloss: 0.689969\n",
      "[37]\tvalid_0's l1: 0.496215\tvalid_0's binary_logloss: 0.689999\n",
      "[38]\tvalid_0's l1: 0.496157\tvalid_0's binary_logloss: 0.690096\n",
      "[39]\tvalid_0's l1: 0.496077\tvalid_0's binary_logloss: 0.690131\n",
      "[40]\tvalid_0's l1: 0.495973\tvalid_0's binary_logloss: 0.690172\n",
      "[41]\tvalid_0's l1: 0.495873\tvalid_0's binary_logloss: 0.690099\n",
      "Early stopping, best iteration is:\n",
      "[36]\tvalid_0's l1: 0.496326\tvalid_0's binary_logloss: 0.689969\n",
      "[1]\tvalid_0's l1: 0.501038\tvalid_0's binary_logloss: 0.695867\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500707\tvalid_0's binary_logloss: 0.695249\n",
      "[3]\tvalid_0's l1: 0.50038\tvalid_0's binary_logloss: 0.694654\n",
      "[4]\tvalid_0's l1: 0.500074\tvalid_0's binary_logloss: 0.694127\n",
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      "[6]\tvalid_0's l1: 0.49947\tvalid_0's binary_logloss: 0.693134\n",
      "[7]\tvalid_0's l1: 0.499172\tvalid_0's binary_logloss: 0.692678\n",
      "[8]\tvalid_0's l1: 0.498909\tvalid_0's binary_logloss: 0.692287\n",
      "[9]\tvalid_0's l1: 0.498618\tvalid_0's binary_logloss: 0.691857\n",
      "[10]\tvalid_0's l1: 0.498334\tvalid_0's binary_logloss: 0.69147\n",
      "[11]\tvalid_0's l1: 0.498024\tvalid_0's binary_logloss: 0.691048\n",
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      "[14]\tvalid_0's l1: 0.497088\tvalid_0's binary_logloss: 0.6898\n",
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      "[17]\tvalid_0's l1: 0.49667\tvalid_0's binary_logloss: 0.689255\n",
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      "[20]\tvalid_0's l1: 0.496205\tvalid_0's binary_logloss: 0.688691\n",
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      "[24]\tvalid_0's l1: 0.495544\tvalid_0's binary_logloss: 0.688043\n",
      "[25]\tvalid_0's l1: 0.495454\tvalid_0's binary_logloss: 0.687998\n",
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      "[28]\tvalid_0's l1: 0.494975\tvalid_0's binary_logloss: 0.687278\n",
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      "[34]\tvalid_0's l1: 0.494042\tvalid_0's binary_logloss: 0.686287\n",
      "[35]\tvalid_0's l1: 0.493944\tvalid_0's binary_logloss: 0.686254\n",
      "[36]\tvalid_0's l1: 0.493781\tvalid_0's binary_logloss: 0.686039\n",
      "[37]\tvalid_0's l1: 0.493683\tvalid_0's binary_logloss: 0.686053\n",
      "[38]\tvalid_0's l1: 0.493547\tvalid_0's binary_logloss: 0.68606\n",
      "[39]\tvalid_0's l1: 0.49344\tvalid_0's binary_logloss: 0.686041\n",
      "[40]\tvalid_0's l1: 0.493287\tvalid_0's binary_logloss: 0.685873\n",
      "[41]\tvalid_0's l1: 0.493129\tvalid_0's binary_logloss: 0.685689\n",
      "[42]\tvalid_0's l1: 0.493049\tvalid_0's binary_logloss: 0.685751\n",
      "[43]\tvalid_0's l1: 0.492794\tvalid_0's binary_logloss: 0.685442\n",
      "[44]\tvalid_0's l1: 0.492687\tvalid_0's binary_logloss: 0.685416\n",
      "[45]\tvalid_0's l1: 0.492525\tvalid_0's binary_logloss: 0.685228\n",
      "[46]\tvalid_0's l1: 0.492288\tvalid_0's binary_logloss: 0.684912\n",
      "[47]\tvalid_0's l1: 0.492135\tvalid_0's binary_logloss: 0.684837\n",
      "[48]\tvalid_0's l1: 0.491868\tvalid_0's binary_logloss: 0.684461\n",
      "[49]\tvalid_0's l1: 0.491739\tvalid_0's binary_logloss: 0.6845\n",
      "[50]\tvalid_0's l1: 0.491601\tvalid_0's binary_logloss: 0.684476\n",
      "[51]\tvalid_0's l1: 0.49132\tvalid_0's binary_logloss: 0.684125\n",
      "[52]\tvalid_0's l1: 0.491049\tvalid_0's binary_logloss: 0.683799\n",
      "[53]\tvalid_0's l1: 0.490913\tvalid_0's binary_logloss: 0.683792\n",
      "[54]\tvalid_0's l1: 0.490654\tvalid_0's binary_logloss: 0.683454\n",
      "[55]\tvalid_0's l1: 0.490533\tvalid_0's binary_logloss: 0.683525\n",
      "[56]\tvalid_0's l1: 0.4904\tvalid_0's binary_logloss: 0.683533\n",
      "[57]\tvalid_0's l1: 0.490115\tvalid_0's binary_logloss: 0.683203\n",
      "[58]\tvalid_0's l1: 0.489855\tvalid_0's binary_logloss: 0.682936\n",
      "[59]\tvalid_0's l1: 0.489738\tvalid_0's binary_logloss: 0.683029\n",
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      "[63]\tvalid_0's l1: 0.4889\tvalid_0's binary_logloss: 0.682375\n",
      "[64]\tvalid_0's l1: 0.488804\tvalid_0's binary_logloss: 0.682455\n",
      "[65]\tvalid_0's l1: 0.488469\tvalid_0's binary_logloss: 0.682062\n",
      "[66]\tvalid_0's l1: 0.488327\tvalid_0's binary_logloss: 0.681987\n",
      "[67]\tvalid_0's l1: 0.488279\tvalid_0's binary_logloss: 0.682109\n",
      "[68]\tvalid_0's l1: 0.487967\tvalid_0's binary_logloss: 0.681775\n",
      "[69]\tvalid_0's l1: 0.487892\tvalid_0's binary_logloss: 0.681866\n",
      "[70]\tvalid_0's l1: 0.487755\tvalid_0's binary_logloss: 0.681815\n",
      "[71]\tvalid_0's l1: 0.487754\tvalid_0's binary_logloss: 0.682011\n",
      "[72]\tvalid_0's l1: 0.487562\tvalid_0's binary_logloss: 0.681882\n",
      "[73]\tvalid_0's l1: 0.487358\tvalid_0's binary_logloss: 0.681773\n",
      "[74]\tvalid_0's l1: 0.487137\tvalid_0's binary_logloss: 0.681544\n",
      "[75]\tvalid_0's l1: 0.487137\tvalid_0's binary_logloss: 0.681748\n",
      "[76]\tvalid_0's l1: 0.486949\tvalid_0's binary_logloss: 0.681641\n",
      "[77]\tvalid_0's l1: 0.486759\tvalid_0's binary_logloss: 0.681563\n",
      "[78]\tvalid_0's l1: 0.486587\tvalid_0's binary_logloss: 0.681461\n",
      "[79]\tvalid_0's l1: 0.48643\tvalid_0's binary_logloss: 0.68142\n",
      "[80]\tvalid_0's l1: 0.486259\tvalid_0's binary_logloss: 0.681207\n",
      "[81]\tvalid_0's l1: 0.486105\tvalid_0's binary_logloss: 0.681183\n",
      "[82]\tvalid_0's l1: 0.486051\tvalid_0's binary_logloss: 0.681228\n",
      "[83]\tvalid_0's l1: 0.485883\tvalid_0's binary_logloss: 0.681022\n",
      "[84]\tvalid_0's l1: 0.48575\tvalid_0's binary_logloss: 0.68106\n",
      "[85]\tvalid_0's l1: 0.485793\tvalid_0's binary_logloss: 0.681347\n",
      "[86]\tvalid_0's l1: 0.485762\tvalid_0's binary_logloss: 0.681429\n",
      "[87]\tvalid_0's l1: 0.485713\tvalid_0's binary_logloss: 0.681602\n",
      "[88]\tvalid_0's l1: 0.485548\tvalid_0's binary_logloss: 0.681403\n",
      "Early stopping, best iteration is:\n",
      "[83]\tvalid_0's l1: 0.485883\tvalid_0's binary_logloss: 0.681022\n",
      "[1]\tvalid_0's l1: 0.501148\tvalid_0's binary_logloss: 0.696029\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501018\tvalid_0's binary_logloss: 0.695742\n",
      "[3]\tvalid_0's l1: 0.500759\tvalid_0's binary_logloss: 0.695198\n",
      "[4]\tvalid_0's l1: 0.500583\tvalid_0's binary_logloss: 0.694829\n",
      "[5]\tvalid_0's l1: 0.500328\tvalid_0's binary_logloss: 0.694308\n",
      "[6]\tvalid_0's l1: 0.500154\tvalid_0's binary_logloss: 0.693954\n",
      "[7]\tvalid_0's l1: 0.499921\tvalid_0's binary_logloss: 0.693482\n",
      "[8]\tvalid_0's l1: 0.4997\tvalid_0's binary_logloss: 0.693048\n",
      "[9]\tvalid_0's l1: 0.49953\tvalid_0's binary_logloss: 0.692711\n",
      "[10]\tvalid_0's l1: 0.499335\tvalid_0's binary_logloss: 0.692334\n",
      "[11]\tvalid_0's l1: 0.499264\tvalid_0's binary_logloss: 0.692194\n",
      "[12]\tvalid_0's l1: 0.499051\tvalid_0's binary_logloss: 0.691787\n",
      "[13]\tvalid_0's l1: 0.498787\tvalid_0's binary_logloss: 0.691245\n",
      "[14]\tvalid_0's l1: 0.498622\tvalid_0's binary_logloss: 0.690931\n",
      "[15]\tvalid_0's l1: 0.498431\tvalid_0's binary_logloss: 0.690585\n",
      "[16]\tvalid_0's l1: 0.498356\tvalid_0's binary_logloss: 0.690421\n",
      "[17]\tvalid_0's l1: 0.498097\tvalid_0's binary_logloss: 0.689925\n",
      "[18]\tvalid_0's l1: 0.497834\tvalid_0's binary_logloss: 0.689402\n",
      "[19]\tvalid_0's l1: 0.497761\tvalid_0's binary_logloss: 0.689275\n",
      "[20]\tvalid_0's l1: 0.497534\tvalid_0's binary_logloss: 0.688864\n",
      "[21]\tvalid_0's l1: 0.497462\tvalid_0's binary_logloss: 0.688746\n",
      "[22]\tvalid_0's l1: 0.497391\tvalid_0's binary_logloss: 0.688613\n",
      "[23]\tvalid_0's l1: 0.497175\tvalid_0's binary_logloss: 0.688218\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[24]\tvalid_0's l1: 0.497106\tvalid_0's binary_logloss: 0.688113\n",
      "[25]\tvalid_0's l1: 0.496911\tvalid_0's binary_logloss: 0.687784\n",
      "[26]\tvalid_0's l1: 0.496695\tvalid_0's binary_logloss: 0.687374\n",
      "[27]\tvalid_0's l1: 0.496503\tvalid_0's binary_logloss: 0.687046\n",
      "[28]\tvalid_0's l1: 0.496301\tvalid_0's binary_logloss: 0.686705\n",
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      "[33]\tvalid_0's l1: 0.495447\tvalid_0's binary_logloss: 0.685234\n",
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      "[35]\tvalid_0's l1: 0.49505\tvalid_0's binary_logloss: 0.68456\n",
      "[36]\tvalid_0's l1: 0.494872\tvalid_0's binary_logloss: 0.684259\n",
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      "[67]\tvalid_0's l1: 0.490959\tvalid_0's binary_logloss: 0.679544\n",
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      "[74]\tvalid_0's l1: 0.490212\tvalid_0's binary_logloss: 0.678899\n",
      "[75]\tvalid_0's l1: 0.490086\tvalid_0's binary_logloss: 0.6787\n",
      "[76]\tvalid_0's l1: 0.489975\tvalid_0's binary_logloss: 0.678733\n",
      "[77]\tvalid_0's l1: 0.48994\tvalid_0's binary_logloss: 0.678704\n",
      "[78]\tvalid_0's l1: 0.48985\tvalid_0's binary_logloss: 0.678745\n",
      "[79]\tvalid_0's l1: 0.489719\tvalid_0's binary_logloss: 0.678536\n",
      "[80]\tvalid_0's l1: 0.489581\tvalid_0's binary_logloss: 0.678555\n",
      "[81]\tvalid_0's l1: 0.489512\tvalid_0's binary_logloss: 0.678442\n",
      "[82]\tvalid_0's l1: 0.489478\tvalid_0's binary_logloss: 0.678418\n",
      "[83]\tvalid_0's l1: 0.48939\tvalid_0's binary_logloss: 0.678477\n",
      "[84]\tvalid_0's l1: 0.489398\tvalid_0's binary_logloss: 0.67858\n",
      "[85]\tvalid_0's l1: 0.489264\tvalid_0's binary_logloss: 0.678621\n",
      "[86]\tvalid_0's l1: 0.4891\tvalid_0's binary_logloss: 0.678342\n",
      "[87]\tvalid_0's l1: 0.488987\tvalid_0's binary_logloss: 0.678441\n",
      "[88]\tvalid_0's l1: 0.488952\tvalid_0's binary_logloss: 0.67842\n",
      "[89]\tvalid_0's l1: 0.488868\tvalid_0's binary_logloss: 0.678507\n",
      "[90]\tvalid_0's l1: 0.488706\tvalid_0's binary_logloss: 0.678235\n",
      "[91]\tvalid_0's l1: 0.488633\tvalid_0's binary_logloss: 0.678311\n",
      "[92]\tvalid_0's l1: 0.488572\tvalid_0's binary_logloss: 0.678208\n",
      "[93]\tvalid_0's l1: 0.488538\tvalid_0's binary_logloss: 0.678192\n",
      "[94]\tvalid_0's l1: 0.488478\tvalid_0's binary_logloss: 0.678366\n",
      "[95]\tvalid_0's l1: 0.488408\tvalid_0's binary_logloss: 0.678459\n",
      "[96]\tvalid_0's l1: 0.488365\tvalid_0's binary_logloss: 0.678426\n",
      "[97]\tvalid_0's l1: 0.488326\tvalid_0's binary_logloss: 0.678418\n",
      "[98]\tvalid_0's l1: 0.488265\tvalid_0's binary_logloss: 0.678637\n",
      "Early stopping, best iteration is:\n",
      "[93]\tvalid_0's l1: 0.488538\tvalid_0's binary_logloss: 0.678192\n",
      "[1]\tvalid_0's l1: 0.501167\tvalid_0's binary_logloss: 0.69602\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501005\tvalid_0's binary_logloss: 0.695667\n",
      "[3]\tvalid_0's l1: 0.500881\tvalid_0's binary_logloss: 0.6954\n",
      "[4]\tvalid_0's l1: 0.500739\tvalid_0's binary_logloss: 0.695106\n",
      "[5]\tvalid_0's l1: 0.500741\tvalid_0's binary_logloss: 0.695112\n",
      "[6]\tvalid_0's l1: 0.500663\tvalid_0's binary_logloss: 0.694968\n",
      "[7]\tvalid_0's l1: 0.500524\tvalid_0's binary_logloss: 0.694701\n",
      "[8]\tvalid_0's l1: 0.500595\tvalid_0's binary_logloss: 0.694829\n",
      "[9]\tvalid_0's l1: 0.500457\tvalid_0's binary_logloss: 0.694579\n",
      "[10]\tvalid_0's l1: 0.500527\tvalid_0's binary_logloss: 0.694722\n",
      "[11]\tvalid_0's l1: 0.500597\tvalid_0's binary_logloss: 0.69488\n",
      "[12]\tvalid_0's l1: 0.500596\tvalid_0's binary_logloss: 0.69489\n",
      "[13]\tvalid_0's l1: 0.500604\tvalid_0's binary_logloss: 0.694917\n",
      "[14]\tvalid_0's l1: 0.500528\tvalid_0's binary_logloss: 0.694815\n",
      "Early stopping, best iteration is:\n",
      "[9]\tvalid_0's l1: 0.500457\tvalid_0's binary_logloss: 0.694579\n",
      "[1]\tvalid_0's l1: 0.501\tvalid_0's binary_logloss: 0.69567\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500713\tvalid_0's binary_logloss: 0.695054\n",
      "[3]\tvalid_0's l1: 0.500464\tvalid_0's binary_logloss: 0.694519\n",
      "[4]\tvalid_0's l1: 0.500188\tvalid_0's binary_logloss: 0.693957\n",
      "[5]\tvalid_0's l1: 0.499944\tvalid_0's binary_logloss: 0.693465\n",
      "[6]\tvalid_0's l1: 0.499667\tvalid_0's binary_logloss: 0.692926\n",
      "[7]\tvalid_0's l1: 0.49937\tvalid_0's binary_logloss: 0.69236\n",
      "[8]\tvalid_0's l1: 0.499134\tvalid_0's binary_logloss: 0.691952\n",
      "[9]\tvalid_0's l1: 0.498876\tvalid_0's binary_logloss: 0.691491\n",
      "[10]\tvalid_0's l1: 0.498836\tvalid_0's binary_logloss: 0.691477\n",
      "[11]\tvalid_0's l1: 0.498797\tvalid_0's binary_logloss: 0.691473\n",
      "[12]\tvalid_0's l1: 0.498558\tvalid_0's binary_logloss: 0.691095\n",
      "[13]\tvalid_0's l1: 0.498519\tvalid_0's binary_logloss: 0.691106\n",
      "[14]\tvalid_0's l1: 0.498529\tvalid_0's binary_logloss: 0.691213\n",
      "[15]\tvalid_0's l1: 0.498514\tvalid_0's binary_logloss: 0.691266\n",
      "[16]\tvalid_0's l1: 0.498477\tvalid_0's binary_logloss: 0.6913\n",
      "[17]\tvalid_0's l1: 0.498462\tvalid_0's binary_logloss: 0.691367\n",
      "Early stopping, best iteration is:\n",
      "[12]\tvalid_0's l1: 0.498558\tvalid_0's binary_logloss: 0.691095\n",
      "[1]\tvalid_0's l1: 0.501151\tvalid_0's binary_logloss: 0.695996\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501011\tvalid_0's binary_logloss: 0.695693\n",
      "[3]\tvalid_0's l1: 0.500896\tvalid_0's binary_logloss: 0.695471\n",
      "[4]\tvalid_0's l1: 0.500764\tvalid_0's binary_logloss: 0.695216\n",
      "[5]\tvalid_0's l1: 0.500666\tvalid_0's binary_logloss: 0.695011\n",
      "[6]\tvalid_0's l1: 0.500574\tvalid_0's binary_logloss: 0.694842\n",
      "[7]\tvalid_0's l1: 0.500439\tvalid_0's binary_logloss: 0.694615\n",
      "[8]\tvalid_0's l1: 0.500349\tvalid_0's binary_logloss: 0.69448\n",
      "[9]\tvalid_0's l1: 0.500216\tvalid_0's binary_logloss: 0.694282\n",
      "[10]\tvalid_0's l1: 0.500128\tvalid_0's binary_logloss: 0.694178\n",
      "[11]\tvalid_0's l1: 0.499997\tvalid_0's binary_logloss: 0.694003\n",
      "[12]\tvalid_0's l1: 0.499743\tvalid_0's binary_logloss: 0.693574\n",
      "[13]\tvalid_0's l1: 0.499709\tvalid_0's binary_logloss: 0.693613\n",
      "[14]\tvalid_0's l1: 0.499633\tvalid_0's binary_logloss: 0.693562\n",
      "[15]\tvalid_0's l1: 0.499333\tvalid_0's binary_logloss: 0.693069\n",
      "[16]\tvalid_0's l1: 0.499208\tvalid_0's binary_logloss: 0.692945\n",
      "[17]\tvalid_0's l1: 0.49894\tvalid_0's binary_logloss: 0.692533\n",
      "[18]\tvalid_0's l1: 0.49882\tvalid_0's binary_logloss: 0.692449\n",
      "[19]\tvalid_0's l1: 0.498762\tvalid_0's binary_logloss: 0.692352\n",
      "[20]\tvalid_0's l1: 0.498711\tvalid_0's binary_logloss: 0.692386\n",
      "[21]\tvalid_0's l1: 0.498511\tvalid_0's binary_logloss: 0.692153\n",
      "[22]\tvalid_0's l1: 0.498434\tvalid_0's binary_logloss: 0.692038\n",
      "[23]\tvalid_0's l1: 0.498177\tvalid_0's binary_logloss: 0.691715\n",
      "[24]\tvalid_0's l1: 0.49812\tvalid_0's binary_logloss: 0.691655\n",
      "[25]\tvalid_0's l1: 0.498046\tvalid_0's binary_logloss: 0.691571\n",
      "[26]\tvalid_0's l1: 0.497846\tvalid_0's binary_logloss: 0.691384\n",
      "[27]\tvalid_0's l1: 0.497775\tvalid_0's binary_logloss: 0.691314\n",
      "[28]\tvalid_0's l1: 0.497474\tvalid_0's binary_logloss: 0.69092\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[29]\tvalid_0's l1: 0.497386\tvalid_0's binary_logloss: 0.690832\n",
      "[30]\tvalid_0's l1: 0.497191\tvalid_0's binary_logloss: 0.690685\n",
      "[31]\tvalid_0's l1: 0.497005\tvalid_0's binary_logloss: 0.690439\n",
      "[32]\tvalid_0's l1: 0.496917\tvalid_0's binary_logloss: 0.690368\n",
      "[33]\tvalid_0's l1: 0.496802\tvalid_0's binary_logloss: 0.690372\n",
      "[34]\tvalid_0's l1: 0.496623\tvalid_0's binary_logloss: 0.690177\n",
      "[35]\tvalid_0's l1: 0.496428\tvalid_0's binary_logloss: 0.690062\n",
      "[36]\tvalid_0's l1: 0.496326\tvalid_0's binary_logloss: 0.689969\n",
      "[37]\tvalid_0's l1: 0.496215\tvalid_0's binary_logloss: 0.689999\n",
      "[38]\tvalid_0's l1: 0.496157\tvalid_0's binary_logloss: 0.690096\n",
      "[39]\tvalid_0's l1: 0.496077\tvalid_0's binary_logloss: 0.690131\n",
      "[40]\tvalid_0's l1: 0.495973\tvalid_0's binary_logloss: 0.690172\n",
      "[41]\tvalid_0's l1: 0.495873\tvalid_0's binary_logloss: 0.690099\n",
      "Early stopping, best iteration is:\n",
      "[36]\tvalid_0's l1: 0.496326\tvalid_0's binary_logloss: 0.689969\n",
      "[1]\tvalid_0's l1: 0.501038\tvalid_0's binary_logloss: 0.695867\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500707\tvalid_0's binary_logloss: 0.695249\n",
      "[3]\tvalid_0's l1: 0.50038\tvalid_0's binary_logloss: 0.694654\n",
      "[4]\tvalid_0's l1: 0.500074\tvalid_0's binary_logloss: 0.694127\n",
      "[5]\tvalid_0's l1: 0.499753\tvalid_0's binary_logloss: 0.693579\n",
      "[6]\tvalid_0's l1: 0.49947\tvalid_0's binary_logloss: 0.693134\n",
      "[7]\tvalid_0's l1: 0.499172\tvalid_0's binary_logloss: 0.692678\n",
      "[8]\tvalid_0's l1: 0.498909\tvalid_0's binary_logloss: 0.692287\n",
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      "[66]\tvalid_0's l1: 0.488327\tvalid_0's binary_logloss: 0.681987\n",
      "[67]\tvalid_0's l1: 0.488279\tvalid_0's binary_logloss: 0.682109\n",
      "[68]\tvalid_0's l1: 0.487967\tvalid_0's binary_logloss: 0.681775\n",
      "[69]\tvalid_0's l1: 0.487892\tvalid_0's binary_logloss: 0.681866\n",
      "[70]\tvalid_0's l1: 0.487755\tvalid_0's binary_logloss: 0.681815\n",
      "[71]\tvalid_0's l1: 0.487754\tvalid_0's binary_logloss: 0.682011\n",
      "[72]\tvalid_0's l1: 0.487562\tvalid_0's binary_logloss: 0.681882\n",
      "[73]\tvalid_0's l1: 0.487358\tvalid_0's binary_logloss: 0.681773\n",
      "[74]\tvalid_0's l1: 0.487137\tvalid_0's binary_logloss: 0.681544\n",
      "[75]\tvalid_0's l1: 0.487137\tvalid_0's binary_logloss: 0.681748\n",
      "[76]\tvalid_0's l1: 0.486949\tvalid_0's binary_logloss: 0.681641\n",
      "[77]\tvalid_0's l1: 0.486759\tvalid_0's binary_logloss: 0.681563\n",
      "[78]\tvalid_0's l1: 0.486587\tvalid_0's binary_logloss: 0.681461\n",
      "[79]\tvalid_0's l1: 0.48643\tvalid_0's binary_logloss: 0.68142\n",
      "[80]\tvalid_0's l1: 0.486259\tvalid_0's binary_logloss: 0.681207\n",
      "[81]\tvalid_0's l1: 0.486105\tvalid_0's binary_logloss: 0.681183\n",
      "[82]\tvalid_0's l1: 0.486051\tvalid_0's binary_logloss: 0.681228\n",
      "[83]\tvalid_0's l1: 0.485883\tvalid_0's binary_logloss: 0.681022\n",
      "[84]\tvalid_0's l1: 0.48575\tvalid_0's binary_logloss: 0.68106\n",
      "[85]\tvalid_0's l1: 0.485793\tvalid_0's binary_logloss: 0.681347\n",
      "[86]\tvalid_0's l1: 0.485762\tvalid_0's binary_logloss: 0.681429\n",
      "[87]\tvalid_0's l1: 0.485713\tvalid_0's binary_logloss: 0.681602\n",
      "[88]\tvalid_0's l1: 0.485548\tvalid_0's binary_logloss: 0.681403\n",
      "Early stopping, best iteration is:\n",
      "[83]\tvalid_0's l1: 0.485883\tvalid_0's binary_logloss: 0.681022\n",
      "[1]\tvalid_0's l1: 0.501148\tvalid_0's binary_logloss: 0.696029\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501018\tvalid_0's binary_logloss: 0.695742\n",
      "[3]\tvalid_0's l1: 0.500759\tvalid_0's binary_logloss: 0.695198\n",
      "[4]\tvalid_0's l1: 0.500583\tvalid_0's binary_logloss: 0.694829\n",
      "[5]\tvalid_0's l1: 0.500328\tvalid_0's binary_logloss: 0.694308\n",
      "[6]\tvalid_0's l1: 0.500154\tvalid_0's binary_logloss: 0.693954\n",
      "[7]\tvalid_0's l1: 0.499921\tvalid_0's binary_logloss: 0.693482\n",
      "[8]\tvalid_0's l1: 0.4997\tvalid_0's binary_logloss: 0.693048\n",
      "[9]\tvalid_0's l1: 0.49953\tvalid_0's binary_logloss: 0.692711\n",
      "[10]\tvalid_0's l1: 0.499335\tvalid_0's binary_logloss: 0.692334\n",
      "[11]\tvalid_0's l1: 0.499264\tvalid_0's binary_logloss: 0.692194\n",
      "[12]\tvalid_0's l1: 0.499051\tvalid_0's binary_logloss: 0.691787\n",
      "[13]\tvalid_0's l1: 0.498787\tvalid_0's binary_logloss: 0.691245\n",
      "[14]\tvalid_0's l1: 0.498622\tvalid_0's binary_logloss: 0.690931\n",
      "[15]\tvalid_0's l1: 0.498431\tvalid_0's binary_logloss: 0.690585\n",
      "[16]\tvalid_0's l1: 0.498356\tvalid_0's binary_logloss: 0.690421\n",
      "[17]\tvalid_0's l1: 0.498097\tvalid_0's binary_logloss: 0.689925\n",
      "[18]\tvalid_0's l1: 0.497834\tvalid_0's binary_logloss: 0.689402\n",
      "[19]\tvalid_0's l1: 0.497761\tvalid_0's binary_logloss: 0.689275\n",
      "[20]\tvalid_0's l1: 0.497534\tvalid_0's binary_logloss: 0.688864\n",
      "[21]\tvalid_0's l1: 0.497462\tvalid_0's binary_logloss: 0.688746\n",
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      "[23]\tvalid_0's l1: 0.497175\tvalid_0's binary_logloss: 0.688218\n",
      "[24]\tvalid_0's l1: 0.497106\tvalid_0's binary_logloss: 0.688113\n",
      "[25]\tvalid_0's l1: 0.496911\tvalid_0's binary_logloss: 0.687784\n",
      "[26]\tvalid_0's l1: 0.496695\tvalid_0's binary_logloss: 0.687374\n",
      "[27]\tvalid_0's l1: 0.496503\tvalid_0's binary_logloss: 0.687046\n",
      "[28]\tvalid_0's l1: 0.496301\tvalid_0's binary_logloss: 0.686705\n",
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      "[37]\tvalid_0's l1: 0.494796\tvalid_0's binary_logloss: 0.684155\n",
      "[38]\tvalid_0's l1: 0.494627\tvalid_0's binary_logloss: 0.683897\n",
      "[39]\tvalid_0's l1: 0.49448\tvalid_0's binary_logloss: 0.683696\n",
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      "[46]\tvalid_0's l1: 0.493313\tvalid_0's binary_logloss: 0.681986\n",
      "[47]\tvalid_0's l1: 0.493196\tvalid_0's binary_logloss: 0.681895\n",
      "[48]\tvalid_0's l1: 0.493021\tvalid_0's binary_logloss: 0.681727\n",
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      "[52]\tvalid_0's l1: 0.492632\tvalid_0's binary_logloss: 0.681128\n",
      "[53]\tvalid_0's l1: 0.492481\tvalid_0's binary_logloss: 0.681016\n",
      "[54]\tvalid_0's l1: 0.492395\tvalid_0's binary_logloss: 0.680909\n",
      "[55]\tvalid_0's l1: 0.492225\tvalid_0's binary_logloss: 0.680777\n",
      "[56]\tvalid_0's l1: 0.491968\tvalid_0's binary_logloss: 0.680371\n",
      "[57]\tvalid_0's l1: 0.491882\tvalid_0's binary_logloss: 0.680248\n",
      "[58]\tvalid_0's l1: 0.491774\tvalid_0's binary_logloss: 0.680215\n",
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      "[66]\tvalid_0's l1: 0.490989\tvalid_0's binary_logloss: 0.679557\n",
      "[67]\tvalid_0's l1: 0.490959\tvalid_0's binary_logloss: 0.679544\n",
      "[68]\tvalid_0's l1: 0.490821\tvalid_0's binary_logloss: 0.679316\n",
      "[69]\tvalid_0's l1: 0.490749\tvalid_0's binary_logloss: 0.679203\n",
      "[70]\tvalid_0's l1: 0.490629\tvalid_0's binary_logloss: 0.679181\n",
      "[71]\tvalid_0's l1: 0.490552\tvalid_0's binary_logloss: 0.679083\n",
      "[72]\tvalid_0's l1: 0.490472\tvalid_0's binary_logloss: 0.679104\n",
      "[73]\tvalid_0's l1: 0.490336\tvalid_0's binary_logloss: 0.678884\n",
      "[74]\tvalid_0's l1: 0.490212\tvalid_0's binary_logloss: 0.678899\n",
      "[75]\tvalid_0's l1: 0.490086\tvalid_0's binary_logloss: 0.6787\n",
      "[76]\tvalid_0's l1: 0.489975\tvalid_0's binary_logloss: 0.678733\n",
      "[77]\tvalid_0's l1: 0.48994\tvalid_0's binary_logloss: 0.678704\n",
      "[78]\tvalid_0's l1: 0.48985\tvalid_0's binary_logloss: 0.678745\n",
      "[79]\tvalid_0's l1: 0.489719\tvalid_0's binary_logloss: 0.678536\n",
      "[80]\tvalid_0's l1: 0.489581\tvalid_0's binary_logloss: 0.678555\n",
      "[81]\tvalid_0's l1: 0.489512\tvalid_0's binary_logloss: 0.678442\n",
      "[82]\tvalid_0's l1: 0.489478\tvalid_0's binary_logloss: 0.678418\n",
      "[83]\tvalid_0's l1: 0.48939\tvalid_0's binary_logloss: 0.678477\n",
      "[84]\tvalid_0's l1: 0.489398\tvalid_0's binary_logloss: 0.67858\n",
      "[85]\tvalid_0's l1: 0.489264\tvalid_0's binary_logloss: 0.678621\n",
      "[86]\tvalid_0's l1: 0.4891\tvalid_0's binary_logloss: 0.678342\n",
      "[87]\tvalid_0's l1: 0.488987\tvalid_0's binary_logloss: 0.678441\n",
      "[88]\tvalid_0's l1: 0.488952\tvalid_0's binary_logloss: 0.67842\n",
      "[89]\tvalid_0's l1: 0.488868\tvalid_0's binary_logloss: 0.678507\n",
      "[90]\tvalid_0's l1: 0.488706\tvalid_0's binary_logloss: 0.678235\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[91]\tvalid_0's l1: 0.488633\tvalid_0's binary_logloss: 0.678311\n",
      "[92]\tvalid_0's l1: 0.488572\tvalid_0's binary_logloss: 0.678208\n",
      "[93]\tvalid_0's l1: 0.488538\tvalid_0's binary_logloss: 0.678192\n",
      "[94]\tvalid_0's l1: 0.488478\tvalid_0's binary_logloss: 0.678366\n",
      "[95]\tvalid_0's l1: 0.488408\tvalid_0's binary_logloss: 0.678459\n",
      "[96]\tvalid_0's l1: 0.488365\tvalid_0's binary_logloss: 0.678426\n",
      "[97]\tvalid_0's l1: 0.488326\tvalid_0's binary_logloss: 0.678418\n",
      "[98]\tvalid_0's l1: 0.488265\tvalid_0's binary_logloss: 0.678637\n",
      "Early stopping, best iteration is:\n",
      "[93]\tvalid_0's l1: 0.488538\tvalid_0's binary_logloss: 0.678192\n",
      "[1]\tvalid_0's l1: 0.501167\tvalid_0's binary_logloss: 0.69602\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501005\tvalid_0's binary_logloss: 0.695667\n",
      "[3]\tvalid_0's l1: 0.500881\tvalid_0's binary_logloss: 0.6954\n",
      "[4]\tvalid_0's l1: 0.500739\tvalid_0's binary_logloss: 0.695106\n",
      "[5]\tvalid_0's l1: 0.500741\tvalid_0's binary_logloss: 0.695112\n",
      "[6]\tvalid_0's l1: 0.500663\tvalid_0's binary_logloss: 0.694968\n",
      "[7]\tvalid_0's l1: 0.500524\tvalid_0's binary_logloss: 0.694701\n",
      "[8]\tvalid_0's l1: 0.500595\tvalid_0's binary_logloss: 0.694829\n",
      "[9]\tvalid_0's l1: 0.500457\tvalid_0's binary_logloss: 0.694579\n",
      "[10]\tvalid_0's l1: 0.500527\tvalid_0's binary_logloss: 0.694722\n",
      "[11]\tvalid_0's l1: 0.500597\tvalid_0's binary_logloss: 0.69488\n",
      "[12]\tvalid_0's l1: 0.500596\tvalid_0's binary_logloss: 0.69489\n",
      "[13]\tvalid_0's l1: 0.500604\tvalid_0's binary_logloss: 0.694917\n",
      "[14]\tvalid_0's l1: 0.500528\tvalid_0's binary_logloss: 0.694815\n",
      "Early stopping, best iteration is:\n",
      "[9]\tvalid_0's l1: 0.500457\tvalid_0's binary_logloss: 0.694579\n",
      "[1]\tvalid_0's l1: 0.501\tvalid_0's binary_logloss: 0.69567\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500713\tvalid_0's binary_logloss: 0.695054\n",
      "[3]\tvalid_0's l1: 0.500464\tvalid_0's binary_logloss: 0.694519\n",
      "[4]\tvalid_0's l1: 0.500188\tvalid_0's binary_logloss: 0.693957\n",
      "[5]\tvalid_0's l1: 0.499944\tvalid_0's binary_logloss: 0.693465\n",
      "[6]\tvalid_0's l1: 0.499667\tvalid_0's binary_logloss: 0.692926\n",
      "[7]\tvalid_0's l1: 0.49937\tvalid_0's binary_logloss: 0.69236\n",
      "[8]\tvalid_0's l1: 0.499134\tvalid_0's binary_logloss: 0.691952\n",
      "[9]\tvalid_0's l1: 0.498876\tvalid_0's binary_logloss: 0.691491\n",
      "[10]\tvalid_0's l1: 0.498836\tvalid_0's binary_logloss: 0.691477\n",
      "[11]\tvalid_0's l1: 0.498797\tvalid_0's binary_logloss: 0.691473\n",
      "[12]\tvalid_0's l1: 0.498558\tvalid_0's binary_logloss: 0.691095\n",
      "[13]\tvalid_0's l1: 0.498519\tvalid_0's binary_logloss: 0.691106\n",
      "[14]\tvalid_0's l1: 0.498529\tvalid_0's binary_logloss: 0.691213\n",
      "[15]\tvalid_0's l1: 0.498514\tvalid_0's binary_logloss: 0.691266\n",
      "[16]\tvalid_0's l1: 0.498477\tvalid_0's binary_logloss: 0.6913\n",
      "[17]\tvalid_0's l1: 0.498462\tvalid_0's binary_logloss: 0.691367\n",
      "Early stopping, best iteration is:\n",
      "[12]\tvalid_0's l1: 0.498558\tvalid_0's binary_logloss: 0.691095\n",
      "[1]\tvalid_0's l1: 0.501151\tvalid_0's binary_logloss: 0.695996\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501011\tvalid_0's binary_logloss: 0.695693\n",
      "[3]\tvalid_0's l1: 0.500896\tvalid_0's binary_logloss: 0.695471\n",
      "[4]\tvalid_0's l1: 0.500764\tvalid_0's binary_logloss: 0.695216\n",
      "[5]\tvalid_0's l1: 0.500666\tvalid_0's binary_logloss: 0.695011\n",
      "[6]\tvalid_0's l1: 0.500574\tvalid_0's binary_logloss: 0.694842\n",
      "[7]\tvalid_0's l1: 0.500439\tvalid_0's binary_logloss: 0.694615\n",
      "[8]\tvalid_0's l1: 0.500349\tvalid_0's binary_logloss: 0.69448\n",
      "[9]\tvalid_0's l1: 0.500216\tvalid_0's binary_logloss: 0.694282\n",
      "[10]\tvalid_0's l1: 0.500128\tvalid_0's binary_logloss: 0.694178\n",
      "[11]\tvalid_0's l1: 0.499997\tvalid_0's binary_logloss: 0.694003\n",
      "[12]\tvalid_0's l1: 0.499743\tvalid_0's binary_logloss: 0.693574\n",
      "[13]\tvalid_0's l1: 0.499709\tvalid_0's binary_logloss: 0.693613\n",
      "[14]\tvalid_0's l1: 0.499633\tvalid_0's binary_logloss: 0.693562\n",
      "[15]\tvalid_0's l1: 0.499333\tvalid_0's binary_logloss: 0.693069\n",
      "[16]\tvalid_0's l1: 0.499208\tvalid_0's binary_logloss: 0.692945\n",
      "[17]\tvalid_0's l1: 0.49894\tvalid_0's binary_logloss: 0.692533\n",
      "[18]\tvalid_0's l1: 0.49882\tvalid_0's binary_logloss: 0.692449\n",
      "[19]\tvalid_0's l1: 0.498762\tvalid_0's binary_logloss: 0.692352\n",
      "[20]\tvalid_0's l1: 0.498711\tvalid_0's binary_logloss: 0.692386\n",
      "[21]\tvalid_0's l1: 0.498511\tvalid_0's binary_logloss: 0.692153\n",
      "[22]\tvalid_0's l1: 0.498434\tvalid_0's binary_logloss: 0.692038\n",
      "[23]\tvalid_0's l1: 0.498177\tvalid_0's binary_logloss: 0.691715\n",
      "[24]\tvalid_0's l1: 0.49812\tvalid_0's binary_logloss: 0.691655\n",
      "[25]\tvalid_0's l1: 0.498046\tvalid_0's binary_logloss: 0.691571\n",
      "[26]\tvalid_0's l1: 0.497846\tvalid_0's binary_logloss: 0.691384\n",
      "[27]\tvalid_0's l1: 0.497775\tvalid_0's binary_logloss: 0.691314\n",
      "[28]\tvalid_0's l1: 0.497474\tvalid_0's binary_logloss: 0.69092\n",
      "[29]\tvalid_0's l1: 0.497386\tvalid_0's binary_logloss: 0.690832\n",
      "[30]\tvalid_0's l1: 0.497191\tvalid_0's binary_logloss: 0.690685\n",
      "[31]\tvalid_0's l1: 0.497005\tvalid_0's binary_logloss: 0.690439\n",
      "[32]\tvalid_0's l1: 0.496917\tvalid_0's binary_logloss: 0.690368\n",
      "[33]\tvalid_0's l1: 0.496802\tvalid_0's binary_logloss: 0.690372\n",
      "[34]\tvalid_0's l1: 0.496623\tvalid_0's binary_logloss: 0.690177\n",
      "[35]\tvalid_0's l1: 0.496428\tvalid_0's binary_logloss: 0.690062\n",
      "[36]\tvalid_0's l1: 0.496326\tvalid_0's binary_logloss: 0.689969\n",
      "[37]\tvalid_0's l1: 0.496215\tvalid_0's binary_logloss: 0.689999\n",
      "[38]\tvalid_0's l1: 0.496157\tvalid_0's binary_logloss: 0.690096\n",
      "[39]\tvalid_0's l1: 0.496077\tvalid_0's binary_logloss: 0.690131\n",
      "[40]\tvalid_0's l1: 0.495973\tvalid_0's binary_logloss: 0.690172\n",
      "[41]\tvalid_0's l1: 0.495873\tvalid_0's binary_logloss: 0.690099\n",
      "Early stopping, best iteration is:\n",
      "[36]\tvalid_0's l1: 0.496326\tvalid_0's binary_logloss: 0.689969\n",
      "[1]\tvalid_0's l1: 0.501038\tvalid_0's binary_logloss: 0.695867\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500707\tvalid_0's binary_logloss: 0.695249\n",
      "[3]\tvalid_0's l1: 0.50038\tvalid_0's binary_logloss: 0.694654\n",
      "[4]\tvalid_0's l1: 0.500074\tvalid_0's binary_logloss: 0.694127\n",
      "[5]\tvalid_0's l1: 0.499753\tvalid_0's binary_logloss: 0.693579\n",
      "[6]\tvalid_0's l1: 0.49947\tvalid_0's binary_logloss: 0.693134\n",
      "[7]\tvalid_0's l1: 0.499172\tvalid_0's binary_logloss: 0.692678\n",
      "[8]\tvalid_0's l1: 0.498909\tvalid_0's binary_logloss: 0.692287\n",
      "[9]\tvalid_0's l1: 0.498618\tvalid_0's binary_logloss: 0.691857\n",
      "[10]\tvalid_0's l1: 0.498334\tvalid_0's binary_logloss: 0.69147\n",
      "[11]\tvalid_0's l1: 0.498024\tvalid_0's binary_logloss: 0.691048\n",
      "[12]\tvalid_0's l1: 0.497763\tvalid_0's binary_logloss: 0.690704\n",
      "[13]\tvalid_0's l1: 0.497441\tvalid_0's binary_logloss: 0.690285\n",
      "[14]\tvalid_0's l1: 0.497088\tvalid_0's binary_logloss: 0.6898\n",
      "[15]\tvalid_0's l1: 0.496962\tvalid_0's binary_logloss: 0.689592\n",
      "[16]\tvalid_0's l1: 0.496837\tvalid_0's binary_logloss: 0.689402\n",
      "[17]\tvalid_0's l1: 0.49667\tvalid_0's binary_logloss: 0.689255\n",
      "[18]\tvalid_0's l1: 0.496527\tvalid_0's binary_logloss: 0.689019\n",
      "[19]\tvalid_0's l1: 0.496326\tvalid_0's binary_logloss: 0.68884\n",
      "[20]\tvalid_0's l1: 0.496205\tvalid_0's binary_logloss: 0.688691\n",
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      "[22]\tvalid_0's l1: 0.495855\tvalid_0's binary_logloss: 0.688319\n",
      "[23]\tvalid_0's l1: 0.495747\tvalid_0's binary_logloss: 0.688238\n",
      "[24]\tvalid_0's l1: 0.495544\tvalid_0's binary_logloss: 0.688043\n",
      "[25]\tvalid_0's l1: 0.495454\tvalid_0's binary_logloss: 0.687998\n",
      "[26]\tvalid_0's l1: 0.495279\tvalid_0's binary_logloss: 0.687703\n",
      "[27]\tvalid_0's l1: 0.495147\tvalid_0's binary_logloss: 0.687556\n",
      "[28]\tvalid_0's l1: 0.494975\tvalid_0's binary_logloss: 0.687278\n",
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      "[34]\tvalid_0's l1: 0.494042\tvalid_0's binary_logloss: 0.686287\n",
      "[35]\tvalid_0's l1: 0.493944\tvalid_0's binary_logloss: 0.686254\n",
      "[36]\tvalid_0's l1: 0.493781\tvalid_0's binary_logloss: 0.686039\n",
      "[37]\tvalid_0's l1: 0.493683\tvalid_0's binary_logloss: 0.686053\n",
      "[38]\tvalid_0's l1: 0.493547\tvalid_0's binary_logloss: 0.68606\n",
      "[39]\tvalid_0's l1: 0.49344\tvalid_0's binary_logloss: 0.686041\n",
      "[40]\tvalid_0's l1: 0.493287\tvalid_0's binary_logloss: 0.685873\n",
      "[41]\tvalid_0's l1: 0.493129\tvalid_0's binary_logloss: 0.685689\n",
      "[42]\tvalid_0's l1: 0.493049\tvalid_0's binary_logloss: 0.685751\n",
      "[43]\tvalid_0's l1: 0.492794\tvalid_0's binary_logloss: 0.685442\n",
      "[44]\tvalid_0's l1: 0.492687\tvalid_0's binary_logloss: 0.685416\n",
      "[45]\tvalid_0's l1: 0.492525\tvalid_0's binary_logloss: 0.685228\n",
      "[46]\tvalid_0's l1: 0.492288\tvalid_0's binary_logloss: 0.684912\n",
      "[47]\tvalid_0's l1: 0.492135\tvalid_0's binary_logloss: 0.684837\n",
      "[48]\tvalid_0's l1: 0.491868\tvalid_0's binary_logloss: 0.684461\n",
      "[49]\tvalid_0's l1: 0.491739\tvalid_0's binary_logloss: 0.6845\n",
      "[50]\tvalid_0's l1: 0.491601\tvalid_0's binary_logloss: 0.684476\n",
      "[51]\tvalid_0's l1: 0.49132\tvalid_0's binary_logloss: 0.684125\n",
      "[52]\tvalid_0's l1: 0.491049\tvalid_0's binary_logloss: 0.683799\n",
      "[53]\tvalid_0's l1: 0.490913\tvalid_0's binary_logloss: 0.683792\n",
      "[54]\tvalid_0's l1: 0.490654\tvalid_0's binary_logloss: 0.683454\n",
      "[55]\tvalid_0's l1: 0.490533\tvalid_0's binary_logloss: 0.683525\n",
      "[56]\tvalid_0's l1: 0.4904\tvalid_0's binary_logloss: 0.683533\n",
      "[57]\tvalid_0's l1: 0.490115\tvalid_0's binary_logloss: 0.683203\n",
      "[58]\tvalid_0's l1: 0.489855\tvalid_0's binary_logloss: 0.682936\n",
      "[59]\tvalid_0's l1: 0.489738\tvalid_0's binary_logloss: 0.683029\n",
      "[60]\tvalid_0's l1: 0.489608\tvalid_0's binary_logloss: 0.683055\n",
      "[61]\tvalid_0's l1: 0.489349\tvalid_0's binary_logloss: 0.682799\n",
      "[62]\tvalid_0's l1: 0.489014\tvalid_0's binary_logloss: 0.682413\n",
      "[63]\tvalid_0's l1: 0.4889\tvalid_0's binary_logloss: 0.682375\n",
      "[64]\tvalid_0's l1: 0.488804\tvalid_0's binary_logloss: 0.682455\n",
      "[65]\tvalid_0's l1: 0.488469\tvalid_0's binary_logloss: 0.682062\n",
      "[66]\tvalid_0's l1: 0.488327\tvalid_0's binary_logloss: 0.681987\n",
      "[67]\tvalid_0's l1: 0.488279\tvalid_0's binary_logloss: 0.682109\n",
      "[68]\tvalid_0's l1: 0.487967\tvalid_0's binary_logloss: 0.681775\n",
      "[69]\tvalid_0's l1: 0.487892\tvalid_0's binary_logloss: 0.681866\n",
      "[70]\tvalid_0's l1: 0.487755\tvalid_0's binary_logloss: 0.681815\n",
      "[71]\tvalid_0's l1: 0.487754\tvalid_0's binary_logloss: 0.682011\n",
      "[72]\tvalid_0's l1: 0.487562\tvalid_0's binary_logloss: 0.681882\n",
      "[73]\tvalid_0's l1: 0.487358\tvalid_0's binary_logloss: 0.681773\n",
      "[74]\tvalid_0's l1: 0.487137\tvalid_0's binary_logloss: 0.681544\n",
      "[75]\tvalid_0's l1: 0.487137\tvalid_0's binary_logloss: 0.681748\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[76]\tvalid_0's l1: 0.486949\tvalid_0's binary_logloss: 0.681641\n",
      "[77]\tvalid_0's l1: 0.486759\tvalid_0's binary_logloss: 0.681563\n",
      "[78]\tvalid_0's l1: 0.486587\tvalid_0's binary_logloss: 0.681461\n",
      "[79]\tvalid_0's l1: 0.48643\tvalid_0's binary_logloss: 0.68142\n",
      "[80]\tvalid_0's l1: 0.486259\tvalid_0's binary_logloss: 0.681207\n",
      "[81]\tvalid_0's l1: 0.486105\tvalid_0's binary_logloss: 0.681183\n",
      "[82]\tvalid_0's l1: 0.486051\tvalid_0's binary_logloss: 0.681228\n",
      "[83]\tvalid_0's l1: 0.485883\tvalid_0's binary_logloss: 0.681022\n",
      "[84]\tvalid_0's l1: 0.48575\tvalid_0's binary_logloss: 0.68106\n",
      "[85]\tvalid_0's l1: 0.485793\tvalid_0's binary_logloss: 0.681347\n",
      "[86]\tvalid_0's l1: 0.485762\tvalid_0's binary_logloss: 0.681429\n",
      "[87]\tvalid_0's l1: 0.485713\tvalid_0's binary_logloss: 0.681602\n",
      "[88]\tvalid_0's l1: 0.485548\tvalid_0's binary_logloss: 0.681403\n",
      "Early stopping, best iteration is:\n",
      "[83]\tvalid_0's l1: 0.485883\tvalid_0's binary_logloss: 0.681022\n",
      "[1]\tvalid_0's l1: 0.501148\tvalid_0's binary_logloss: 0.696029\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501018\tvalid_0's binary_logloss: 0.695742\n",
      "[3]\tvalid_0's l1: 0.500759\tvalid_0's binary_logloss: 0.695198\n",
      "[4]\tvalid_0's l1: 0.500583\tvalid_0's binary_logloss: 0.694829\n",
      "[5]\tvalid_0's l1: 0.500328\tvalid_0's binary_logloss: 0.694308\n",
      "[6]\tvalid_0's l1: 0.500154\tvalid_0's binary_logloss: 0.693954\n",
      "[7]\tvalid_0's l1: 0.499921\tvalid_0's binary_logloss: 0.693482\n",
      "[8]\tvalid_0's l1: 0.4997\tvalid_0's binary_logloss: 0.693048\n",
      "[9]\tvalid_0's l1: 0.49953\tvalid_0's binary_logloss: 0.692711\n",
      "[10]\tvalid_0's l1: 0.499335\tvalid_0's binary_logloss: 0.692334\n",
      "[11]\tvalid_0's l1: 0.499264\tvalid_0's binary_logloss: 0.692194\n",
      "[12]\tvalid_0's l1: 0.499051\tvalid_0's binary_logloss: 0.691787\n",
      "[13]\tvalid_0's l1: 0.498787\tvalid_0's binary_logloss: 0.691245\n",
      "[14]\tvalid_0's l1: 0.498622\tvalid_0's binary_logloss: 0.690931\n",
      "[15]\tvalid_0's l1: 0.498431\tvalid_0's binary_logloss: 0.690585\n",
      "[16]\tvalid_0's l1: 0.498356\tvalid_0's binary_logloss: 0.690421\n",
      "[17]\tvalid_0's l1: 0.498097\tvalid_0's binary_logloss: 0.689925\n",
      "[18]\tvalid_0's l1: 0.497834\tvalid_0's binary_logloss: 0.689402\n",
      "[19]\tvalid_0's l1: 0.497761\tvalid_0's binary_logloss: 0.689275\n",
      "[20]\tvalid_0's l1: 0.497534\tvalid_0's binary_logloss: 0.688864\n",
      "[21]\tvalid_0's l1: 0.497462\tvalid_0's binary_logloss: 0.688746\n",
      "[22]\tvalid_0's l1: 0.497391\tvalid_0's binary_logloss: 0.688613\n",
      "[23]\tvalid_0's l1: 0.497175\tvalid_0's binary_logloss: 0.688218\n",
      "[24]\tvalid_0's l1: 0.497106\tvalid_0's binary_logloss: 0.688113\n",
      "[25]\tvalid_0's l1: 0.496911\tvalid_0's binary_logloss: 0.687784\n",
      "[26]\tvalid_0's l1: 0.496695\tvalid_0's binary_logloss: 0.687374\n",
      "[27]\tvalid_0's l1: 0.496503\tvalid_0's binary_logloss: 0.687046\n",
      "[28]\tvalid_0's l1: 0.496301\tvalid_0's binary_logloss: 0.686705\n",
      "[29]\tvalid_0's l1: 0.496086\tvalid_0's binary_logloss: 0.686307\n",
      "[30]\tvalid_0's l1: 0.4959\tvalid_0's binary_logloss: 0.686001\n",
      "[31]\tvalid_0's l1: 0.495839\tvalid_0's binary_logloss: 0.685909\n",
      "[32]\tvalid_0's l1: 0.495622\tvalid_0's binary_logloss: 0.68555\n",
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      "[35]\tvalid_0's l1: 0.49505\tvalid_0's binary_logloss: 0.68456\n",
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      "[38]\tvalid_0's l1: 0.494627\tvalid_0's binary_logloss: 0.683897\n",
      "[39]\tvalid_0's l1: 0.49448\tvalid_0's binary_logloss: 0.683696\n",
      "[40]\tvalid_0's l1: 0.49436\tvalid_0's binary_logloss: 0.683506\n",
      "[41]\tvalid_0's l1: 0.494175\tvalid_0's binary_logloss: 0.683266\n",
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      "[56]\tvalid_0's l1: 0.491968\tvalid_0's binary_logloss: 0.680371\n",
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      "[77]\tvalid_0's l1: 0.48994\tvalid_0's binary_logloss: 0.678704\n",
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      "[79]\tvalid_0's l1: 0.489719\tvalid_0's binary_logloss: 0.678536\n",
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      "[82]\tvalid_0's l1: 0.489478\tvalid_0's binary_logloss: 0.678418\n",
      "[83]\tvalid_0's l1: 0.48939\tvalid_0's binary_logloss: 0.678477\n",
      "[84]\tvalid_0's l1: 0.489398\tvalid_0's binary_logloss: 0.67858\n",
      "[85]\tvalid_0's l1: 0.489264\tvalid_0's binary_logloss: 0.678621\n",
      "[86]\tvalid_0's l1: 0.4891\tvalid_0's binary_logloss: 0.678342\n",
      "[87]\tvalid_0's l1: 0.488987\tvalid_0's binary_logloss: 0.678441\n",
      "[88]\tvalid_0's l1: 0.488952\tvalid_0's binary_logloss: 0.67842\n",
      "[89]\tvalid_0's l1: 0.488868\tvalid_0's binary_logloss: 0.678507\n",
      "[90]\tvalid_0's l1: 0.488706\tvalid_0's binary_logloss: 0.678235\n",
      "[91]\tvalid_0's l1: 0.488633\tvalid_0's binary_logloss: 0.678311\n",
      "[92]\tvalid_0's l1: 0.488572\tvalid_0's binary_logloss: 0.678208\n",
      "[93]\tvalid_0's l1: 0.488538\tvalid_0's binary_logloss: 0.678192\n",
      "[94]\tvalid_0's l1: 0.488478\tvalid_0's binary_logloss: 0.678366\n",
      "[95]\tvalid_0's l1: 0.488408\tvalid_0's binary_logloss: 0.678459\n",
      "[96]\tvalid_0's l1: 0.488365\tvalid_0's binary_logloss: 0.678426\n",
      "[97]\tvalid_0's l1: 0.488326\tvalid_0's binary_logloss: 0.678418\n",
      "[98]\tvalid_0's l1: 0.488265\tvalid_0's binary_logloss: 0.678637\n",
      "Early stopping, best iteration is:\n",
      "[93]\tvalid_0's l1: 0.488538\tvalid_0's binary_logloss: 0.678192\n",
      "[1]\tvalid_0's l1: 0.501167\tvalid_0's binary_logloss: 0.69602\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501005\tvalid_0's binary_logloss: 0.695667\n",
      "[3]\tvalid_0's l1: 0.500881\tvalid_0's binary_logloss: 0.6954\n",
      "[4]\tvalid_0's l1: 0.500739\tvalid_0's binary_logloss: 0.695106\n",
      "[5]\tvalid_0's l1: 0.500741\tvalid_0's binary_logloss: 0.695112\n",
      "[6]\tvalid_0's l1: 0.500663\tvalid_0's binary_logloss: 0.694968\n",
      "[7]\tvalid_0's l1: 0.500524\tvalid_0's binary_logloss: 0.694701\n",
      "[8]\tvalid_0's l1: 0.500595\tvalid_0's binary_logloss: 0.694829\n",
      "[9]\tvalid_0's l1: 0.500457\tvalid_0's binary_logloss: 0.694579\n",
      "[10]\tvalid_0's l1: 0.500527\tvalid_0's binary_logloss: 0.694722\n",
      "[11]\tvalid_0's l1: 0.500597\tvalid_0's binary_logloss: 0.69488\n",
      "[12]\tvalid_0's l1: 0.500596\tvalid_0's binary_logloss: 0.69489\n",
      "[13]\tvalid_0's l1: 0.500604\tvalid_0's binary_logloss: 0.694917\n",
      "[14]\tvalid_0's l1: 0.500528\tvalid_0's binary_logloss: 0.694815\n",
      "Early stopping, best iteration is:\n",
      "[9]\tvalid_0's l1: 0.500457\tvalid_0's binary_logloss: 0.694579\n",
      "[1]\tvalid_0's l1: 0.501\tvalid_0's binary_logloss: 0.69567\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500713\tvalid_0's binary_logloss: 0.695054\n",
      "[3]\tvalid_0's l1: 0.500464\tvalid_0's binary_logloss: 0.694519\n",
      "[4]\tvalid_0's l1: 0.500188\tvalid_0's binary_logloss: 0.693957\n",
      "[5]\tvalid_0's l1: 0.499944\tvalid_0's binary_logloss: 0.693465\n",
      "[6]\tvalid_0's l1: 0.499667\tvalid_0's binary_logloss: 0.692926\n",
      "[7]\tvalid_0's l1: 0.49937\tvalid_0's binary_logloss: 0.69236\n",
      "[8]\tvalid_0's l1: 0.499134\tvalid_0's binary_logloss: 0.691952\n",
      "[9]\tvalid_0's l1: 0.498876\tvalid_0's binary_logloss: 0.691491\n",
      "[10]\tvalid_0's l1: 0.498836\tvalid_0's binary_logloss: 0.691477\n",
      "[11]\tvalid_0's l1: 0.498797\tvalid_0's binary_logloss: 0.691473\n",
      "[12]\tvalid_0's l1: 0.498558\tvalid_0's binary_logloss: 0.691095\n",
      "[13]\tvalid_0's l1: 0.498519\tvalid_0's binary_logloss: 0.691106\n",
      "[14]\tvalid_0's l1: 0.498529\tvalid_0's binary_logloss: 0.691213\n",
      "[15]\tvalid_0's l1: 0.498514\tvalid_0's binary_logloss: 0.691266\n",
      "[16]\tvalid_0's l1: 0.498477\tvalid_0's binary_logloss: 0.6913\n",
      "[17]\tvalid_0's l1: 0.498462\tvalid_0's binary_logloss: 0.691367\n",
      "Early stopping, best iteration is:\n",
      "[12]\tvalid_0's l1: 0.498558\tvalid_0's binary_logloss: 0.691095\n",
      "[1]\tvalid_0's l1: 0.501182\tvalid_0's binary_logloss: 0.696082\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501073\tvalid_0's binary_logloss: 0.695879\n",
      "[3]\tvalid_0's l1: 0.500988\tvalid_0's binary_logloss: 0.695703\n",
      "[4]\tvalid_0's l1: 0.500884\tvalid_0's binary_logloss: 0.695538\n",
      "[5]\tvalid_0's l1: 0.500784\tvalid_0's binary_logloss: 0.695323\n",
      "[6]\tvalid_0's l1: 0.500685\tvalid_0's binary_logloss: 0.695136\n",
      "[7]\tvalid_0's l1: 0.500591\tvalid_0's binary_logloss: 0.694986\n",
      "[8]\tvalid_0's l1: 0.500489\tvalid_0's binary_logloss: 0.694829\n",
      "[9]\tvalid_0's l1: 0.50041\tvalid_0's binary_logloss: 0.694733\n",
      "[10]\tvalid_0's l1: 0.500074\tvalid_0's binary_logloss: 0.694049\n",
      "[11]\tvalid_0's l1: 0.499963\tvalid_0's binary_logloss: 0.693916\n",
      "[12]\tvalid_0's l1: 0.499619\tvalid_0's binary_logloss: 0.693224\n",
      "[13]\tvalid_0's l1: 0.499487\tvalid_0's binary_logloss: 0.693074\n",
      "[14]\tvalid_0's l1: 0.499395\tvalid_0's binary_logloss: 0.69299\n",
      "[15]\tvalid_0's l1: 0.499178\tvalid_0's binary_logloss: 0.692686\n",
      "[16]\tvalid_0's l1: 0.498841\tvalid_0's binary_logloss: 0.692018\n",
      "[17]\tvalid_0's l1: 0.498758\tvalid_0's binary_logloss: 0.69198\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[18]\tvalid_0's l1: 0.498686\tvalid_0's binary_logloss: 0.692\n",
      "[19]\tvalid_0's l1: 0.498562\tvalid_0's binary_logloss: 0.691822\n",
      "[20]\tvalid_0's l1: 0.498373\tvalid_0's binary_logloss: 0.691624\n",
      "[21]\tvalid_0's l1: 0.498329\tvalid_0's binary_logloss: 0.691738\n",
      "[22]\tvalid_0's l1: 0.498207\tvalid_0's binary_logloss: 0.691594\n",
      "[23]\tvalid_0's l1: 0.498012\tvalid_0's binary_logloss: 0.691432\n",
      "[24]\tvalid_0's l1: 0.497893\tvalid_0's binary_logloss: 0.691317\n",
      "[25]\tvalid_0's l1: 0.497706\tvalid_0's binary_logloss: 0.691179\n",
      "[26]\tvalid_0's l1: 0.497515\tvalid_0's binary_logloss: 0.691066\n",
      "[27]\tvalid_0's l1: 0.497388\tvalid_0's binary_logloss: 0.690936\n",
      "[28]\tvalid_0's l1: 0.497212\tvalid_0's binary_logloss: 0.690849\n",
      "[29]\tvalid_0's l1: 0.497094\tvalid_0's binary_logloss: 0.690757\n",
      "[30]\tvalid_0's l1: 0.496965\tvalid_0's binary_logloss: 0.69079\n",
      "[31]\tvalid_0's l1: 0.496881\tvalid_0's binary_logloss: 0.690896\n",
      "[32]\tvalid_0's l1: 0.496776\tvalid_0's binary_logloss: 0.690881\n",
      "[33]\tvalid_0's l1: 0.496677\tvalid_0's binary_logloss: 0.690995\n",
      "[34]\tvalid_0's l1: 0.496566\tvalid_0's binary_logloss: 0.690989\n",
      "Early stopping, best iteration is:\n",
      "[29]\tvalid_0's l1: 0.497094\tvalid_0's binary_logloss: 0.690757\n",
      "[1]\tvalid_0's l1: 0.501023\tvalid_0's binary_logloss: 0.695841\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500733\tvalid_0's binary_logloss: 0.6953\n",
      "[3]\tvalid_0's l1: 0.500415\tvalid_0's binary_logloss: 0.694709\n",
      "[4]\tvalid_0's l1: 0.500148\tvalid_0's binary_logloss: 0.694267\n",
      "[5]\tvalid_0's l1: 0.499836\tvalid_0's binary_logloss: 0.69373\n",
      "[6]\tvalid_0's l1: 0.499575\tvalid_0's binary_logloss: 0.693341\n",
      "[7]\tvalid_0's l1: 0.499282\tvalid_0's binary_logloss: 0.692879\n",
      "[8]\tvalid_0's l1: 0.499094\tvalid_0's binary_logloss: 0.69265\n",
      "[9]\tvalid_0's l1: 0.498849\tvalid_0's binary_logloss: 0.69232\n",
      "[10]\tvalid_0's l1: 0.498665\tvalid_0's binary_logloss: 0.692129\n",
      "[11]\tvalid_0's l1: 0.498382\tvalid_0's binary_logloss: 0.691748\n",
      "[12]\tvalid_0's l1: 0.498012\tvalid_0's binary_logloss: 0.691198\n",
      "[13]\tvalid_0's l1: 0.497732\tvalid_0's binary_logloss: 0.690849\n",
      "[14]\tvalid_0's l1: 0.497554\tvalid_0's binary_logloss: 0.690583\n",
      "[15]\tvalid_0's l1: 0.497379\tvalid_0's binary_logloss: 0.69034\n",
      "[16]\tvalid_0's l1: 0.497218\tvalid_0's binary_logloss: 0.690146\n",
      "[17]\tvalid_0's l1: 0.497086\tvalid_0's binary_logloss: 0.690009\n",
      "[18]\tvalid_0's l1: 0.496941\tvalid_0's binary_logloss: 0.689882\n",
      "[19]\tvalid_0's l1: 0.496774\tvalid_0's binary_logloss: 0.689727\n",
      "[20]\tvalid_0's l1: 0.496632\tvalid_0's binary_logloss: 0.689641\n",
      "[21]\tvalid_0's l1: 0.496531\tvalid_0's binary_logloss: 0.689633\n",
      "[22]\tvalid_0's l1: 0.49643\tvalid_0's binary_logloss: 0.689566\n",
      "[23]\tvalid_0's l1: 0.496323\tvalid_0's binary_logloss: 0.68949\n",
      "[24]\tvalid_0's l1: 0.496004\tvalid_0's binary_logloss: 0.689148\n",
      "[25]\tvalid_0's l1: 0.495848\tvalid_0's binary_logloss: 0.689036\n",
      "[26]\tvalid_0's l1: 0.49575\tvalid_0's binary_logloss: 0.688981\n",
      "[27]\tvalid_0's l1: 0.495654\tvalid_0's binary_logloss: 0.688962\n",
      "[28]\tvalid_0's l1: 0.495601\tvalid_0's binary_logloss: 0.689001\n",
      "[29]\tvalid_0's l1: 0.4955\tvalid_0's binary_logloss: 0.688945\n",
      "[30]\tvalid_0's l1: 0.495301\tvalid_0's binary_logloss: 0.688823\n",
      "[31]\tvalid_0's l1: 0.49522\tvalid_0's binary_logloss: 0.688865\n",
      "[32]\tvalid_0's l1: 0.49511\tvalid_0's binary_logloss: 0.688851\n",
      "[33]\tvalid_0's l1: 0.494931\tvalid_0's binary_logloss: 0.688814\n",
      "[34]\tvalid_0's l1: 0.494864\tvalid_0's binary_logloss: 0.688899\n",
      "[35]\tvalid_0's l1: 0.494688\tvalid_0's binary_logloss: 0.688887\n",
      "[36]\tvalid_0's l1: 0.494644\tvalid_0's binary_logloss: 0.689028\n",
      "[37]\tvalid_0's l1: 0.494539\tvalid_0's binary_logloss: 0.689028\n",
      "[38]\tvalid_0's l1: 0.494408\tvalid_0's binary_logloss: 0.688962\n",
      "Early stopping, best iteration is:\n",
      "[33]\tvalid_0's l1: 0.494931\tvalid_0's binary_logloss: 0.688814\n",
      "[1]\tvalid_0's l1: 0.501059\tvalid_0's binary_logloss: 0.695877\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500792\tvalid_0's binary_logloss: 0.69535\n",
      "[3]\tvalid_0's l1: 0.500528\tvalid_0's binary_logloss: 0.694837\n",
      "[4]\tvalid_0's l1: 0.500165\tvalid_0's binary_logloss: 0.694078\n",
      "[5]\tvalid_0's l1: 0.499825\tvalid_0's binary_logloss: 0.693403\n",
      "[6]\tvalid_0's l1: 0.499567\tvalid_0's binary_logloss: 0.692919\n",
      "[7]\tvalid_0's l1: 0.499207\tvalid_0's binary_logloss: 0.692231\n",
      "[8]\tvalid_0's l1: 0.499002\tvalid_0's binary_logloss: 0.691876\n",
      "[9]\tvalid_0's l1: 0.498683\tvalid_0's binary_logloss: 0.691296\n",
      "[10]\tvalid_0's l1: 0.498595\tvalid_0's binary_logloss: 0.691118\n",
      "[11]\tvalid_0's l1: 0.498273\tvalid_0's binary_logloss: 0.690553\n",
      "[12]\tvalid_0's l1: 0.498075\tvalid_0's binary_logloss: 0.690227\n",
      "[13]\tvalid_0's l1: 0.497777\tvalid_0's binary_logloss: 0.689745\n",
      "[14]\tvalid_0's l1: 0.497693\tvalid_0's binary_logloss: 0.689588\n",
      "[15]\tvalid_0's l1: 0.497422\tvalid_0's binary_logloss: 0.689174\n",
      "[16]\tvalid_0's l1: 0.49723\tvalid_0's binary_logloss: 0.688876\n",
      "[17]\tvalid_0's l1: 0.496957\tvalid_0's binary_logloss: 0.688479\n",
      "[18]\tvalid_0's l1: 0.496877\tvalid_0's binary_logloss: 0.688341\n",
      "[19]\tvalid_0's l1: 0.496592\tvalid_0's binary_logloss: 0.68794\n",
      "[20]\tvalid_0's l1: 0.496407\tvalid_0's binary_logloss: 0.687668\n",
      "[21]\tvalid_0's l1: 0.496136\tvalid_0's binary_logloss: 0.68731\n",
      "[22]\tvalid_0's l1: 0.49606\tvalid_0's binary_logloss: 0.687188\n",
      "[23]\tvalid_0's l1: 0.495752\tvalid_0's binary_logloss: 0.686706\n",
      "[24]\tvalid_0's l1: 0.49557\tvalid_0's binary_logloss: 0.686394\n",
      "[25]\tvalid_0's l1: 0.495324\tvalid_0's binary_logloss: 0.686104\n",
      "[26]\tvalid_0's l1: 0.495106\tvalid_0's binary_logloss: 0.685772\n",
      "[27]\tvalid_0's l1: 0.494851\tvalid_0's binary_logloss: 0.685489\n",
      "[28]\tvalid_0's l1: 0.494775\tvalid_0's binary_logloss: 0.685409\n",
      "[29]\tvalid_0's l1: 0.494488\tvalid_0's binary_logloss: 0.685007\n",
      "[30]\tvalid_0's l1: 0.494389\tvalid_0's binary_logloss: 0.684902\n",
      "[31]\tvalid_0's l1: 0.494161\tvalid_0's binary_logloss: 0.684665\n",
      "[32]\tvalid_0's l1: 0.494105\tvalid_0's binary_logloss: 0.68474\n",
      "[33]\tvalid_0's l1: 0.493956\tvalid_0's binary_logloss: 0.684535\n",
      "[34]\tvalid_0's l1: 0.493776\tvalid_0's binary_logloss: 0.684263\n",
      "[35]\tvalid_0's l1: 0.493496\tvalid_0's binary_logloss: 0.683914\n",
      "[36]\tvalid_0's l1: 0.493485\tvalid_0's binary_logloss: 0.684086\n",
      "[37]\tvalid_0's l1: 0.493267\tvalid_0's binary_logloss: 0.683764\n",
      "[38]\tvalid_0's l1: 0.493088\tvalid_0's binary_logloss: 0.683502\n",
      "[39]\tvalid_0's l1: 0.492852\tvalid_0's binary_logloss: 0.683125\n",
      "[40]\tvalid_0's l1: 0.492634\tvalid_0's binary_logloss: 0.682925\n",
      "[41]\tvalid_0's l1: 0.492436\tvalid_0's binary_logloss: 0.682549\n",
      "[42]\tvalid_0's l1: 0.492194\tvalid_0's binary_logloss: 0.682111\n",
      "[43]\tvalid_0's l1: 0.492\tvalid_0's binary_logloss: 0.68178\n",
      "[44]\tvalid_0's l1: 0.491842\tvalid_0's binary_logloss: 0.681609\n",
      "[45]\tvalid_0's l1: 0.491661\tvalid_0's binary_logloss: 0.681271\n",
      "[46]\tvalid_0's l1: 0.491455\tvalid_0's binary_logloss: 0.680877\n",
      "[47]\tvalid_0's l1: 0.491174\tvalid_0's binary_logloss: 0.680414\n",
      "[48]\tvalid_0's l1: 0.490943\tvalid_0's binary_logloss: 0.68006\n",
      "[49]\tvalid_0's l1: 0.490707\tvalid_0's binary_logloss: 0.679862\n",
      "[50]\tvalid_0's l1: 0.490479\tvalid_0's binary_logloss: 0.679517\n",
      "[51]\tvalid_0's l1: 0.490313\tvalid_0's binary_logloss: 0.679306\n",
      "[52]\tvalid_0's l1: 0.490208\tvalid_0's binary_logloss: 0.679196\n",
      "[53]\tvalid_0's l1: 0.489906\tvalid_0's binary_logloss: 0.678806\n",
      "[54]\tvalid_0's l1: 0.489737\tvalid_0's binary_logloss: 0.678682\n",
      "[55]\tvalid_0's l1: 0.489695\tvalid_0's binary_logloss: 0.6787\n",
      "[56]\tvalid_0's l1: 0.489399\tvalid_0's binary_logloss: 0.678369\n",
      "[57]\tvalid_0's l1: 0.489234\tvalid_0's binary_logloss: 0.678299\n",
      "[58]\tvalid_0's l1: 0.489061\tvalid_0's binary_logloss: 0.678024\n",
      "[59]\tvalid_0's l1: 0.48889\tvalid_0's binary_logloss: 0.677972\n",
      "[60]\tvalid_0's l1: 0.488852\tvalid_0's binary_logloss: 0.678014\n",
      "[61]\tvalid_0's l1: 0.488566\tvalid_0's binary_logloss: 0.677764\n",
      "[62]\tvalid_0's l1: 0.4884\tvalid_0's binary_logloss: 0.677763\n",
      "[63]\tvalid_0's l1: 0.488169\tvalid_0's binary_logloss: 0.677607\n",
      "[64]\tvalid_0's l1: 0.487942\tvalid_0's binary_logloss: 0.677213\n",
      "[65]\tvalid_0's l1: 0.487737\tvalid_0's binary_logloss: 0.677199\n",
      "[66]\tvalid_0's l1: 0.487574\tvalid_0's binary_logloss: 0.677183\n",
      "[67]\tvalid_0's l1: 0.487388\tvalid_0's binary_logloss: 0.676848\n",
      "[68]\tvalid_0's l1: 0.487145\tvalid_0's binary_logloss: 0.67667\n",
      "[69]\tvalid_0's l1: 0.486931\tvalid_0's binary_logloss: 0.676461\n",
      "[70]\tvalid_0's l1: 0.486716\tvalid_0's binary_logloss: 0.676247\n",
      "[71]\tvalid_0's l1: 0.486564\tvalid_0's binary_logloss: 0.676086\n",
      "[72]\tvalid_0's l1: 0.486293\tvalid_0's binary_logloss: 0.675568\n",
      "[73]\tvalid_0's l1: 0.486089\tvalid_0's binary_logloss: 0.675237\n",
      "[74]\tvalid_0's l1: 0.486112\tvalid_0's binary_logloss: 0.675499\n",
      "[75]\tvalid_0's l1: 0.485844\tvalid_0's binary_logloss: 0.674997\n",
      "[76]\tvalid_0's l1: 0.485809\tvalid_0's binary_logloss: 0.675179\n",
      "[77]\tvalid_0's l1: 0.485813\tvalid_0's binary_logloss: 0.675434\n",
      "[78]\tvalid_0's l1: 0.485793\tvalid_0's binary_logloss: 0.675519\n",
      "[79]\tvalid_0's l1: 0.485586\tvalid_0's binary_logloss: 0.675146\n",
      "[80]\tvalid_0's l1: 0.485529\tvalid_0's binary_logloss: 0.675303\n",
      "Early stopping, best iteration is:\n",
      "[75]\tvalid_0's l1: 0.485844\tvalid_0's binary_logloss: 0.674997\n",
      "[1]\tvalid_0's l1: 0.501037\tvalid_0's binary_logloss: 0.695769\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500797\tvalid_0's binary_logloss: 0.69527\n",
      "[3]\tvalid_0's l1: 0.500554\tvalid_0's binary_logloss: 0.694783\n",
      "[4]\tvalid_0's l1: 0.50048\tvalid_0's binary_logloss: 0.694633\n",
      "[5]\tvalid_0's l1: 0.500387\tvalid_0's binary_logloss: 0.694468\n",
      "[6]\tvalid_0's l1: 0.500453\tvalid_0's binary_logloss: 0.694621\n",
      "[7]\tvalid_0's l1: 0.500514\tvalid_0's binary_logloss: 0.694782\n",
      "[8]\tvalid_0's l1: 0.500457\tvalid_0's binary_logloss: 0.694724\n",
      "[9]\tvalid_0's l1: 0.500507\tvalid_0's binary_logloss: 0.694816\n",
      "[10]\tvalid_0's l1: 0.500413\tvalid_0's binary_logloss: 0.694642\n",
      "Early stopping, best iteration is:\n",
      "[5]\tvalid_0's l1: 0.500387\tvalid_0's binary_logloss: 0.694468\n",
      "[1]\tvalid_0's l1: 0.50108\tvalid_0's binary_logloss: 0.695823\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500872\tvalid_0's binary_logloss: 0.695376\n",
      "[3]\tvalid_0's l1: 0.50058\tvalid_0's binary_logloss: 0.694758\n",
      "[4]\tvalid_0's l1: 0.500335\tvalid_0's binary_logloss: 0.694294\n",
      "[5]\tvalid_0's l1: 0.500093\tvalid_0's binary_logloss: 0.69384\n",
      "[6]\tvalid_0's l1: 0.499801\tvalid_0's binary_logloss: 0.693316\n",
      "[7]\tvalid_0's l1: 0.499607\tvalid_0's binary_logloss: 0.693034\n",
      "[8]\tvalid_0's l1: 0.499328\tvalid_0's binary_logloss: 0.692587\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[9]\tvalid_0's l1: 0.49916\tvalid_0's binary_logloss: 0.692406\n",
      "[10]\tvalid_0's l1: 0.498886\tvalid_0's binary_logloss: 0.691969\n",
      "[11]\tvalid_0's l1: 0.498666\tvalid_0's binary_logloss: 0.691683\n",
      "[12]\tvalid_0's l1: 0.49836\tvalid_0's binary_logloss: 0.691218\n",
      "[13]\tvalid_0's l1: 0.498014\tvalid_0's binary_logloss: 0.690696\n",
      "[14]\tvalid_0's l1: 0.497963\tvalid_0's binary_logloss: 0.690723\n",
      "[15]\tvalid_0's l1: 0.497823\tvalid_0's binary_logloss: 0.690562\n",
      "[16]\tvalid_0's l1: 0.497799\tvalid_0's binary_logloss: 0.690672\n",
      "[17]\tvalid_0's l1: 0.497662\tvalid_0's binary_logloss: 0.690546\n",
      "[18]\tvalid_0's l1: 0.49764\tvalid_0's binary_logloss: 0.690689\n",
      "[19]\tvalid_0's l1: 0.497504\tvalid_0's binary_logloss: 0.690605\n",
      "[20]\tvalid_0's l1: 0.497488\tvalid_0's binary_logloss: 0.690745\n",
      "[21]\tvalid_0's l1: 0.497355\tvalid_0's binary_logloss: 0.690686\n",
      "[22]\tvalid_0's l1: 0.497228\tvalid_0's binary_logloss: 0.690657\n",
      "Early stopping, best iteration is:\n",
      "[17]\tvalid_0's l1: 0.497662\tvalid_0's binary_logloss: 0.690546\n",
      "[1]\tvalid_0's l1: 0.501182\tvalid_0's binary_logloss: 0.696082\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501073\tvalid_0's binary_logloss: 0.695876\n",
      "[3]\tvalid_0's l1: 0.500996\tvalid_0's binary_logloss: 0.695717\n",
      "[4]\tvalid_0's l1: 0.500898\tvalid_0's binary_logloss: 0.695563\n",
      "[5]\tvalid_0's l1: 0.500798\tvalid_0's binary_logloss: 0.695349\n",
      "[6]\tvalid_0's l1: 0.500698\tvalid_0's binary_logloss: 0.695162\n",
      "[7]\tvalid_0's l1: 0.500605\tvalid_0's binary_logloss: 0.695011\n",
      "[8]\tvalid_0's l1: 0.500508\tvalid_0's binary_logloss: 0.694866\n",
      "[9]\tvalid_0's l1: 0.500424\tvalid_0's binary_logloss: 0.694759\n",
      "[10]\tvalid_0's l1: 0.500087\tvalid_0's binary_logloss: 0.694075\n",
      "[11]\tvalid_0's l1: 0.499977\tvalid_0's binary_logloss: 0.693942\n",
      "[12]\tvalid_0's l1: 0.499633\tvalid_0's binary_logloss: 0.693251\n",
      "[13]\tvalid_0's l1: 0.499501\tvalid_0's binary_logloss: 0.693101\n",
      "[14]\tvalid_0's l1: 0.499409\tvalid_0's binary_logloss: 0.693017\n",
      "[15]\tvalid_0's l1: 0.499192\tvalid_0's binary_logloss: 0.692713\n",
      "[16]\tvalid_0's l1: 0.498855\tvalid_0's binary_logloss: 0.692045\n",
      "[17]\tvalid_0's l1: 0.498766\tvalid_0's binary_logloss: 0.691996\n",
      "[18]\tvalid_0's l1: 0.498695\tvalid_0's binary_logloss: 0.692016\n",
      "[19]\tvalid_0's l1: 0.49857\tvalid_0's binary_logloss: 0.691837\n",
      "[20]\tvalid_0's l1: 0.498381\tvalid_0's binary_logloss: 0.691639\n",
      "[21]\tvalid_0's l1: 0.498265\tvalid_0's binary_logloss: 0.691607\n",
      "[22]\tvalid_0's l1: 0.498144\tvalid_0's binary_logloss: 0.691464\n",
      "[23]\tvalid_0's l1: 0.497901\tvalid_0's binary_logloss: 0.691201\n",
      "[24]\tvalid_0's l1: 0.497771\tvalid_0's binary_logloss: 0.691046\n",
      "[25]\tvalid_0's l1: 0.497702\tvalid_0's binary_logloss: 0.691148\n",
      "[26]\tvalid_0's l1: 0.497512\tvalid_0's binary_logloss: 0.691032\n",
      "[27]\tvalid_0's l1: 0.497395\tvalid_0's binary_logloss: 0.69095\n",
      "[28]\tvalid_0's l1: 0.497219\tvalid_0's binary_logloss: 0.690863\n",
      "[29]\tvalid_0's l1: 0.497035\tvalid_0's binary_logloss: 0.690812\n",
      "[30]\tvalid_0's l1: 0.496927\tvalid_0's binary_logloss: 0.690773\n",
      "[31]\tvalid_0's l1: 0.496906\tvalid_0's binary_logloss: 0.690997\n",
      "[32]\tvalid_0's l1: 0.496801\tvalid_0's binary_logloss: 0.690981\n",
      "[33]\tvalid_0's l1: 0.496752\tvalid_0's binary_logloss: 0.691188\n",
      "[34]\tvalid_0's l1: 0.496642\tvalid_0's binary_logloss: 0.691183\n",
      "[35]\tvalid_0's l1: 0.496498\tvalid_0's binary_logloss: 0.691208\n",
      "Early stopping, best iteration is:\n",
      "[30]\tvalid_0's l1: 0.496927\tvalid_0's binary_logloss: 0.690773\n",
      "[1]\tvalid_0's l1: 0.501\tvalid_0's binary_logloss: 0.695793\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500688\tvalid_0's binary_logloss: 0.695206\n",
      "[3]\tvalid_0's l1: 0.500347\tvalid_0's binary_logloss: 0.694573\n",
      "[4]\tvalid_0's l1: 0.500059\tvalid_0's binary_logloss: 0.694089\n",
      "[5]\tvalid_0's l1: 0.499725\tvalid_0's binary_logloss: 0.693513\n",
      "[6]\tvalid_0's l1: 0.49944\tvalid_0's binary_logloss: 0.693082\n",
      "[7]\tvalid_0's l1: 0.499152\tvalid_0's binary_logloss: 0.692649\n",
      "[8]\tvalid_0's l1: 0.498924\tvalid_0's binary_logloss: 0.69235\n",
      "[9]\tvalid_0's l1: 0.498724\tvalid_0's binary_logloss: 0.69209\n",
      "[10]\tvalid_0's l1: 0.498351\tvalid_0's binary_logloss: 0.691533\n",
      "[11]\tvalid_0's l1: 0.498196\tvalid_0's binary_logloss: 0.691399\n",
      "[12]\tvalid_0's l1: 0.497905\tvalid_0's binary_logloss: 0.691039\n",
      "[13]\tvalid_0's l1: 0.497565\tvalid_0's binary_logloss: 0.690567\n",
      "[14]\tvalid_0's l1: 0.497219\tvalid_0's binary_logloss: 0.690101\n",
      "[15]\tvalid_0's l1: 0.497032\tvalid_0's binary_logloss: 0.689824\n",
      "[16]\tvalid_0's l1: 0.496848\tvalid_0's binary_logloss: 0.689571\n",
      "[17]\tvalid_0's l1: 0.496676\tvalid_0's binary_logloss: 0.689362\n",
      "[18]\tvalid_0's l1: 0.496531\tvalid_0's binary_logloss: 0.689223\n",
      "[19]\tvalid_0's l1: 0.496394\tvalid_0's binary_logloss: 0.689099\n",
      "[20]\tvalid_0's l1: 0.496265\tvalid_0's binary_logloss: 0.689025\n",
      "[21]\tvalid_0's l1: 0.496078\tvalid_0's binary_logloss: 0.688857\n",
      "[22]\tvalid_0's l1: 0.495983\tvalid_0's binary_logloss: 0.688867\n",
      "[23]\tvalid_0's l1: 0.495806\tvalid_0's binary_logloss: 0.688751\n",
      "[24]\tvalid_0's l1: 0.49568\tvalid_0's binary_logloss: 0.688658\n",
      "[25]\tvalid_0's l1: 0.495549\tvalid_0's binary_logloss: 0.688514\n",
      "[26]\tvalid_0's l1: 0.495437\tvalid_0's binary_logloss: 0.688464\n",
      "[27]\tvalid_0's l1: 0.495361\tvalid_0's binary_logloss: 0.68854\n",
      "[28]\tvalid_0's l1: 0.495321\tvalid_0's binary_logloss: 0.688585\n",
      "[29]\tvalid_0's l1: 0.495207\tvalid_0's binary_logloss: 0.6885\n",
      "[30]\tvalid_0's l1: 0.495077\tvalid_0's binary_logloss: 0.688437\n",
      "[31]\tvalid_0's l1: 0.494997\tvalid_0's binary_logloss: 0.688482\n",
      "[32]\tvalid_0's l1: 0.494938\tvalid_0's binary_logloss: 0.688596\n",
      "[33]\tvalid_0's l1: 0.494759\tvalid_0's binary_logloss: 0.688554\n",
      "[34]\tvalid_0's l1: 0.494662\tvalid_0's binary_logloss: 0.688536\n",
      "[35]\tvalid_0's l1: 0.494537\tvalid_0's binary_logloss: 0.688529\n",
      "Early stopping, best iteration is:\n",
      "[30]\tvalid_0's l1: 0.495077\tvalid_0's binary_logloss: 0.688437\n",
      "[1]\tvalid_0's l1: 0.501059\tvalid_0's binary_logloss: 0.695877\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500792\tvalid_0's binary_logloss: 0.69535\n",
      "[3]\tvalid_0's l1: 0.500528\tvalid_0's binary_logloss: 0.694837\n",
      "[4]\tvalid_0's l1: 0.500132\tvalid_0's binary_logloss: 0.694018\n",
      "[5]\tvalid_0's l1: 0.499714\tvalid_0's binary_logloss: 0.693199\n",
      "[6]\tvalid_0's l1: 0.499456\tvalid_0's binary_logloss: 0.692716\n",
      "[7]\tvalid_0's l1: 0.499033\tvalid_0's binary_logloss: 0.691912\n",
      "[8]\tvalid_0's l1: 0.498829\tvalid_0's binary_logloss: 0.691559\n",
      "[9]\tvalid_0's l1: 0.498469\tvalid_0's binary_logloss: 0.690902\n",
      "[10]\tvalid_0's l1: 0.498382\tvalid_0's binary_logloss: 0.690723\n",
      "[11]\tvalid_0's l1: 0.498012\tvalid_0's binary_logloss: 0.690066\n",
      "[12]\tvalid_0's l1: 0.497839\tvalid_0's binary_logloss: 0.689741\n",
      "[13]\tvalid_0's l1: 0.497524\tvalid_0's binary_logloss: 0.689216\n",
      "[14]\tvalid_0's l1: 0.49733\tvalid_0's binary_logloss: 0.688906\n",
      "[15]\tvalid_0's l1: 0.496991\tvalid_0's binary_logloss: 0.68835\n",
      "[16]\tvalid_0's l1: 0.496811\tvalid_0's binary_logloss: 0.688019\n",
      "[17]\tvalid_0's l1: 0.496534\tvalid_0's binary_logloss: 0.68759\n",
      "[18]\tvalid_0's l1: 0.496316\tvalid_0's binary_logloss: 0.687135\n",
      "[19]\tvalid_0's l1: 0.495956\tvalid_0's binary_logloss: 0.686441\n",
      "[20]\tvalid_0's l1: 0.495617\tvalid_0's binary_logloss: 0.685924\n",
      "[21]\tvalid_0's l1: 0.495319\tvalid_0's binary_logloss: 0.6855\n",
      "[22]\tvalid_0's l1: 0.495132\tvalid_0's binary_logloss: 0.685178\n",
      "[23]\tvalid_0's l1: 0.494789\tvalid_0's binary_logloss: 0.684686\n",
      "[24]\tvalid_0's l1: 0.49456\tvalid_0's binary_logloss: 0.684245\n",
      "[25]\tvalid_0's l1: 0.494355\tvalid_0's binary_logloss: 0.683899\n",
      "[26]\tvalid_0's l1: 0.494248\tvalid_0's binary_logloss: 0.683756\n",
      "[27]\tvalid_0's l1: 0.493961\tvalid_0's binary_logloss: 0.683359\n",
      "[28]\tvalid_0's l1: 0.493782\tvalid_0's binary_logloss: 0.683073\n",
      "[29]\tvalid_0's l1: 0.493458\tvalid_0's binary_logloss: 0.682659\n",
      "[30]\tvalid_0's l1: 0.493296\tvalid_0's binary_logloss: 0.682451\n",
      "[31]\tvalid_0's l1: 0.493025\tvalid_0's binary_logloss: 0.6821\n",
      "[32]\tvalid_0's l1: 0.492859\tvalid_0's binary_logloss: 0.681884\n",
      "[33]\tvalid_0's l1: 0.492671\tvalid_0's binary_logloss: 0.681616\n",
      "[34]\tvalid_0's l1: 0.492521\tvalid_0's binary_logloss: 0.681326\n",
      "[35]\tvalid_0's l1: 0.492325\tvalid_0's binary_logloss: 0.681099\n",
      "[36]\tvalid_0's l1: 0.492141\tvalid_0's binary_logloss: 0.68084\n",
      "[37]\tvalid_0's l1: 0.491978\tvalid_0's binary_logloss: 0.68064\n",
      "[38]\tvalid_0's l1: 0.491689\tvalid_0's binary_logloss: 0.680165\n",
      "[39]\tvalid_0's l1: 0.49164\tvalid_0's binary_logloss: 0.680163\n",
      "[40]\tvalid_0's l1: 0.491473\tvalid_0's binary_logloss: 0.679946\n",
      "[41]\tvalid_0's l1: 0.491229\tvalid_0's binary_logloss: 0.679497\n",
      "[42]\tvalid_0's l1: 0.490988\tvalid_0's binary_logloss: 0.679073\n",
      "[43]\tvalid_0's l1: 0.490776\tvalid_0's binary_logloss: 0.678708\n",
      "[44]\tvalid_0's l1: 0.490418\tvalid_0's binary_logloss: 0.678144\n",
      "[45]\tvalid_0's l1: 0.490264\tvalid_0's binary_logloss: 0.67797\n",
      "[46]\tvalid_0's l1: 0.490051\tvalid_0's binary_logloss: 0.677627\n",
      "[47]\tvalid_0's l1: 0.489816\tvalid_0's binary_logloss: 0.677271\n",
      "[48]\tvalid_0's l1: 0.489601\tvalid_0's binary_logloss: 0.67695\n",
      "[49]\tvalid_0's l1: 0.489454\tvalid_0's binary_logloss: 0.676806\n",
      "[50]\tvalid_0's l1: 0.489185\tvalid_0's binary_logloss: 0.676426\n",
      "[51]\tvalid_0's l1: 0.489023\tvalid_0's binary_logloss: 0.676251\n",
      "[52]\tvalid_0's l1: 0.488809\tvalid_0's binary_logloss: 0.67603\n",
      "[53]\tvalid_0's l1: 0.48854\tvalid_0's binary_logloss: 0.675591\n",
      "[54]\tvalid_0's l1: 0.488333\tvalid_0's binary_logloss: 0.675407\n",
      "[55]\tvalid_0's l1: 0.488277\tvalid_0's binary_logloss: 0.675373\n",
      "[56]\tvalid_0's l1: 0.488113\tvalid_0's binary_logloss: 0.675294\n",
      "[57]\tvalid_0's l1: 0.487899\tvalid_0's binary_logloss: 0.67515\n",
      "[58]\tvalid_0's l1: 0.487749\tvalid_0's binary_logloss: 0.675151\n",
      "[59]\tvalid_0's l1: 0.487696\tvalid_0's binary_logloss: 0.675141\n",
      "[60]\tvalid_0's l1: 0.487531\tvalid_0's binary_logloss: 0.675131\n",
      "[61]\tvalid_0's l1: 0.487334\tvalid_0's binary_logloss: 0.675094\n",
      "[62]\tvalid_0's l1: 0.487244\tvalid_0's binary_logloss: 0.674955\n",
      "[63]\tvalid_0's l1: 0.487155\tvalid_0's binary_logloss: 0.674836\n",
      "[64]\tvalid_0's l1: 0.487122\tvalid_0's binary_logloss: 0.67488\n",
      "[65]\tvalid_0's l1: 0.486985\tvalid_0's binary_logloss: 0.674948\n",
      "[66]\tvalid_0's l1: 0.486898\tvalid_0's binary_logloss: 0.674846\n",
      "[67]\tvalid_0's l1: 0.48685\tvalid_0's binary_logloss: 0.674861\n",
      "[68]\tvalid_0's l1: 0.486814\tvalid_0's binary_logloss: 0.675031\n",
      "Early stopping, best iteration is:\n",
      "[63]\tvalid_0's l1: 0.487155\tvalid_0's binary_logloss: 0.674836\n",
      "[1]\tvalid_0's l1: 0.501037\tvalid_0's binary_logloss: 0.695769\n",
      "Training until validation scores don't improve for 5 rounds.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2]\tvalid_0's l1: 0.500797\tvalid_0's binary_logloss: 0.69527\n",
      "[3]\tvalid_0's l1: 0.500554\tvalid_0's binary_logloss: 0.694783\n",
      "[4]\tvalid_0's l1: 0.50048\tvalid_0's binary_logloss: 0.694633\n",
      "[5]\tvalid_0's l1: 0.500387\tvalid_0's binary_logloss: 0.694468\n",
      "[6]\tvalid_0's l1: 0.500453\tvalid_0's binary_logloss: 0.694621\n",
      "[7]\tvalid_0's l1: 0.500514\tvalid_0's binary_logloss: 0.694782\n",
      "[8]\tvalid_0's l1: 0.500457\tvalid_0's binary_logloss: 0.694724\n",
      "[9]\tvalid_0's l1: 0.500495\tvalid_0's binary_logloss: 0.694795\n",
      "[10]\tvalid_0's l1: 0.500397\tvalid_0's binary_logloss: 0.69462\n",
      "Early stopping, best iteration is:\n",
      "[5]\tvalid_0's l1: 0.500387\tvalid_0's binary_logloss: 0.694468\n",
      "[1]\tvalid_0's l1: 0.50108\tvalid_0's binary_logloss: 0.695823\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500872\tvalid_0's binary_logloss: 0.695376\n",
      "[3]\tvalid_0's l1: 0.50058\tvalid_0's binary_logloss: 0.694758\n",
      "[4]\tvalid_0's l1: 0.500335\tvalid_0's binary_logloss: 0.694294\n",
      "[5]\tvalid_0's l1: 0.500093\tvalid_0's binary_logloss: 0.69384\n",
      "[6]\tvalid_0's l1: 0.499801\tvalid_0's binary_logloss: 0.693316\n",
      "[7]\tvalid_0's l1: 0.499607\tvalid_0's binary_logloss: 0.693034\n",
      "[8]\tvalid_0's l1: 0.499328\tvalid_0's binary_logloss: 0.692587\n",
      "[9]\tvalid_0's l1: 0.49916\tvalid_0's binary_logloss: 0.692406\n",
      "[10]\tvalid_0's l1: 0.498886\tvalid_0's binary_logloss: 0.691969\n",
      "[11]\tvalid_0's l1: 0.498643\tvalid_0's binary_logloss: 0.691638\n",
      "[12]\tvalid_0's l1: 0.498311\tvalid_0's binary_logloss: 0.691128\n",
      "[13]\tvalid_0's l1: 0.497963\tvalid_0's binary_logloss: 0.690614\n",
      "[14]\tvalid_0's l1: 0.497912\tvalid_0's binary_logloss: 0.690641\n",
      "[15]\tvalid_0's l1: 0.497772\tvalid_0's binary_logloss: 0.69048\n",
      "[16]\tvalid_0's l1: 0.497748\tvalid_0's binary_logloss: 0.690591\n",
      "[17]\tvalid_0's l1: 0.497611\tvalid_0's binary_logloss: 0.690466\n",
      "[18]\tvalid_0's l1: 0.497475\tvalid_0's binary_logloss: 0.690367\n",
      "[19]\tvalid_0's l1: 0.497453\tvalid_0's binary_logloss: 0.690525\n",
      "[20]\tvalid_0's l1: 0.497402\tvalid_0's binary_logloss: 0.690599\n",
      "[21]\tvalid_0's l1: 0.497268\tvalid_0's binary_logloss: 0.690542\n",
      "[22]\tvalid_0's l1: 0.497142\tvalid_0's binary_logloss: 0.690513\n",
      "[23]\tvalid_0's l1: 0.49716\tvalid_0's binary_logloss: 0.690653\n",
      "Early stopping, best iteration is:\n",
      "[18]\tvalid_0's l1: 0.497475\tvalid_0's binary_logloss: 0.690367\n",
      "[1]\tvalid_0's l1: 0.501182\tvalid_0's binary_logloss: 0.696082\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501073\tvalid_0's binary_logloss: 0.695876\n",
      "[3]\tvalid_0's l1: 0.500996\tvalid_0's binary_logloss: 0.695717\n",
      "[4]\tvalid_0's l1: 0.500898\tvalid_0's binary_logloss: 0.695563\n",
      "[5]\tvalid_0's l1: 0.500798\tvalid_0's binary_logloss: 0.695349\n",
      "[6]\tvalid_0's l1: 0.500698\tvalid_0's binary_logloss: 0.695162\n",
      "[7]\tvalid_0's l1: 0.500605\tvalid_0's binary_logloss: 0.695011\n",
      "[8]\tvalid_0's l1: 0.500508\tvalid_0's binary_logloss: 0.694866\n",
      "[9]\tvalid_0's l1: 0.500424\tvalid_0's binary_logloss: 0.694759\n",
      "[10]\tvalid_0's l1: 0.500087\tvalid_0's binary_logloss: 0.694075\n",
      "[11]\tvalid_0's l1: 0.499977\tvalid_0's binary_logloss: 0.693942\n",
      "[12]\tvalid_0's l1: 0.499633\tvalid_0's binary_logloss: 0.693251\n",
      "[13]\tvalid_0's l1: 0.499501\tvalid_0's binary_logloss: 0.693101\n",
      "[14]\tvalid_0's l1: 0.499409\tvalid_0's binary_logloss: 0.693017\n",
      "[15]\tvalid_0's l1: 0.499192\tvalid_0's binary_logloss: 0.692713\n",
      "[16]\tvalid_0's l1: 0.498855\tvalid_0's binary_logloss: 0.692045\n",
      "[17]\tvalid_0's l1: 0.498766\tvalid_0's binary_logloss: 0.691996\n",
      "[18]\tvalid_0's l1: 0.498695\tvalid_0's binary_logloss: 0.692016\n",
      "[19]\tvalid_0's l1: 0.49857\tvalid_0's binary_logloss: 0.691837\n",
      "[20]\tvalid_0's l1: 0.498381\tvalid_0's binary_logloss: 0.691639\n",
      "[21]\tvalid_0's l1: 0.498265\tvalid_0's binary_logloss: 0.691607\n",
      "[22]\tvalid_0's l1: 0.498144\tvalid_0's binary_logloss: 0.691464\n",
      "[23]\tvalid_0's l1: 0.497901\tvalid_0's binary_logloss: 0.691201\n",
      "[24]\tvalid_0's l1: 0.497771\tvalid_0's binary_logloss: 0.691046\n",
      "[25]\tvalid_0's l1: 0.497702\tvalid_0's binary_logloss: 0.691148\n",
      "[26]\tvalid_0's l1: 0.497512\tvalid_0's binary_logloss: 0.691032\n",
      "[27]\tvalid_0's l1: 0.497395\tvalid_0's binary_logloss: 0.69095\n",
      "[28]\tvalid_0's l1: 0.497219\tvalid_0's binary_logloss: 0.690863\n",
      "[29]\tvalid_0's l1: 0.497035\tvalid_0's binary_logloss: 0.690812\n",
      "[30]\tvalid_0's l1: 0.496927\tvalid_0's binary_logloss: 0.690773\n",
      "[31]\tvalid_0's l1: 0.496906\tvalid_0's binary_logloss: 0.690997\n",
      "[32]\tvalid_0's l1: 0.496801\tvalid_0's binary_logloss: 0.690981\n",
      "[33]\tvalid_0's l1: 0.496752\tvalid_0's binary_logloss: 0.691188\n",
      "[34]\tvalid_0's l1: 0.496642\tvalid_0's binary_logloss: 0.691183\n",
      "[35]\tvalid_0's l1: 0.496498\tvalid_0's binary_logloss: 0.691208\n",
      "Early stopping, best iteration is:\n",
      "[30]\tvalid_0's l1: 0.496927\tvalid_0's binary_logloss: 0.690773\n",
      "[1]\tvalid_0's l1: 0.501\tvalid_0's binary_logloss: 0.695793\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500688\tvalid_0's binary_logloss: 0.695206\n",
      "[3]\tvalid_0's l1: 0.500347\tvalid_0's binary_logloss: 0.694573\n",
      "[4]\tvalid_0's l1: 0.500059\tvalid_0's binary_logloss: 0.694089\n",
      "[5]\tvalid_0's l1: 0.499725\tvalid_0's binary_logloss: 0.693513\n",
      "[6]\tvalid_0's l1: 0.49944\tvalid_0's binary_logloss: 0.693082\n",
      "[7]\tvalid_0's l1: 0.499152\tvalid_0's binary_logloss: 0.692649\n",
      "[8]\tvalid_0's l1: 0.498924\tvalid_0's binary_logloss: 0.69235\n",
      "[9]\tvalid_0's l1: 0.498724\tvalid_0's binary_logloss: 0.69209\n",
      "[10]\tvalid_0's l1: 0.498351\tvalid_0's binary_logloss: 0.691533\n",
      "[11]\tvalid_0's l1: 0.498196\tvalid_0's binary_logloss: 0.691399\n",
      "[12]\tvalid_0's l1: 0.497905\tvalid_0's binary_logloss: 0.691039\n",
      "[13]\tvalid_0's l1: 0.497565\tvalid_0's binary_logloss: 0.690567\n",
      "[14]\tvalid_0's l1: 0.497219\tvalid_0's binary_logloss: 0.690101\n",
      "[15]\tvalid_0's l1: 0.497032\tvalid_0's binary_logloss: 0.689824\n",
      "[16]\tvalid_0's l1: 0.496848\tvalid_0's binary_logloss: 0.689571\n",
      "[17]\tvalid_0's l1: 0.496676\tvalid_0's binary_logloss: 0.689362\n",
      "[18]\tvalid_0's l1: 0.496531\tvalid_0's binary_logloss: 0.689223\n",
      "[19]\tvalid_0's l1: 0.496394\tvalid_0's binary_logloss: 0.689099\n",
      "[20]\tvalid_0's l1: 0.496265\tvalid_0's binary_logloss: 0.689025\n",
      "[21]\tvalid_0's l1: 0.496078\tvalid_0's binary_logloss: 0.688857\n",
      "[22]\tvalid_0's l1: 0.495983\tvalid_0's binary_logloss: 0.688867\n",
      "[23]\tvalid_0's l1: 0.495806\tvalid_0's binary_logloss: 0.688751\n",
      "[24]\tvalid_0's l1: 0.49568\tvalid_0's binary_logloss: 0.688658\n",
      "[25]\tvalid_0's l1: 0.495549\tvalid_0's binary_logloss: 0.688514\n",
      "[26]\tvalid_0's l1: 0.495437\tvalid_0's binary_logloss: 0.688464\n",
      "[27]\tvalid_0's l1: 0.495361\tvalid_0's binary_logloss: 0.68854\n",
      "[28]\tvalid_0's l1: 0.495321\tvalid_0's binary_logloss: 0.688585\n",
      "[29]\tvalid_0's l1: 0.495207\tvalid_0's binary_logloss: 0.6885\n",
      "[30]\tvalid_0's l1: 0.495077\tvalid_0's binary_logloss: 0.688437\n",
      "[31]\tvalid_0's l1: 0.494997\tvalid_0's binary_logloss: 0.688482\n",
      "[32]\tvalid_0's l1: 0.494938\tvalid_0's binary_logloss: 0.688596\n",
      "[33]\tvalid_0's l1: 0.494759\tvalid_0's binary_logloss: 0.688554\n",
      "[34]\tvalid_0's l1: 0.494662\tvalid_0's binary_logloss: 0.688536\n",
      "[35]\tvalid_0's l1: 0.494537\tvalid_0's binary_logloss: 0.688529\n",
      "Early stopping, best iteration is:\n",
      "[30]\tvalid_0's l1: 0.495077\tvalid_0's binary_logloss: 0.688437\n",
      "[1]\tvalid_0's l1: 0.501059\tvalid_0's binary_logloss: 0.695877\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500792\tvalid_0's binary_logloss: 0.69535\n",
      "[3]\tvalid_0's l1: 0.500528\tvalid_0's binary_logloss: 0.694837\n",
      "[4]\tvalid_0's l1: 0.500132\tvalid_0's binary_logloss: 0.694018\n",
      "[5]\tvalid_0's l1: 0.499714\tvalid_0's binary_logloss: 0.693199\n",
      "[6]\tvalid_0's l1: 0.499456\tvalid_0's binary_logloss: 0.692716\n",
      "[7]\tvalid_0's l1: 0.499033\tvalid_0's binary_logloss: 0.691912\n",
      "[8]\tvalid_0's l1: 0.498829\tvalid_0's binary_logloss: 0.691559\n",
      "[9]\tvalid_0's l1: 0.498469\tvalid_0's binary_logloss: 0.690902\n",
      "[10]\tvalid_0's l1: 0.498382\tvalid_0's binary_logloss: 0.690723\n",
      "[11]\tvalid_0's l1: 0.498012\tvalid_0's binary_logloss: 0.690066\n",
      "[12]\tvalid_0's l1: 0.497839\tvalid_0's binary_logloss: 0.689741\n",
      "[13]\tvalid_0's l1: 0.497524\tvalid_0's binary_logloss: 0.689216\n",
      "[14]\tvalid_0's l1: 0.49733\tvalid_0's binary_logloss: 0.688906\n",
      "[15]\tvalid_0's l1: 0.496991\tvalid_0's binary_logloss: 0.68835\n",
      "[16]\tvalid_0's l1: 0.496811\tvalid_0's binary_logloss: 0.688019\n",
      "[17]\tvalid_0's l1: 0.496534\tvalid_0's binary_logloss: 0.68759\n",
      "[18]\tvalid_0's l1: 0.496316\tvalid_0's binary_logloss: 0.687135\n",
      "[19]\tvalid_0's l1: 0.495956\tvalid_0's binary_logloss: 0.686441\n",
      "[20]\tvalid_0's l1: 0.495617\tvalid_0's binary_logloss: 0.685924\n",
      "[21]\tvalid_0's l1: 0.495319\tvalid_0's binary_logloss: 0.6855\n",
      "[22]\tvalid_0's l1: 0.495132\tvalid_0's binary_logloss: 0.685178\n",
      "[23]\tvalid_0's l1: 0.494789\tvalid_0's binary_logloss: 0.684686\n",
      "[24]\tvalid_0's l1: 0.49456\tvalid_0's binary_logloss: 0.684245\n",
      "[25]\tvalid_0's l1: 0.494355\tvalid_0's binary_logloss: 0.683899\n",
      "[26]\tvalid_0's l1: 0.494248\tvalid_0's binary_logloss: 0.683756\n",
      "[27]\tvalid_0's l1: 0.493961\tvalid_0's binary_logloss: 0.683359\n",
      "[28]\tvalid_0's l1: 0.493782\tvalid_0's binary_logloss: 0.683073\n",
      "[29]\tvalid_0's l1: 0.493458\tvalid_0's binary_logloss: 0.682659\n",
      "[30]\tvalid_0's l1: 0.493296\tvalid_0's binary_logloss: 0.682451\n",
      "[31]\tvalid_0's l1: 0.493025\tvalid_0's binary_logloss: 0.6821\n",
      "[32]\tvalid_0's l1: 0.492859\tvalid_0's binary_logloss: 0.681884\n",
      "[33]\tvalid_0's l1: 0.492671\tvalid_0's binary_logloss: 0.681616\n",
      "[34]\tvalid_0's l1: 0.492521\tvalid_0's binary_logloss: 0.681326\n",
      "[35]\tvalid_0's l1: 0.492325\tvalid_0's binary_logloss: 0.681099\n",
      "[36]\tvalid_0's l1: 0.492141\tvalid_0's binary_logloss: 0.68084\n",
      "[37]\tvalid_0's l1: 0.491978\tvalid_0's binary_logloss: 0.68064\n",
      "[38]\tvalid_0's l1: 0.491689\tvalid_0's binary_logloss: 0.680165\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[39]\tvalid_0's l1: 0.49164\tvalid_0's binary_logloss: 0.680163\n",
      "[40]\tvalid_0's l1: 0.491473\tvalid_0's binary_logloss: 0.679946\n",
      "[41]\tvalid_0's l1: 0.491229\tvalid_0's binary_logloss: 0.679497\n",
      "[42]\tvalid_0's l1: 0.490988\tvalid_0's binary_logloss: 0.679073\n",
      "[43]\tvalid_0's l1: 0.490776\tvalid_0's binary_logloss: 0.678708\n",
      "[44]\tvalid_0's l1: 0.490418\tvalid_0's binary_logloss: 0.678144\n",
      "[45]\tvalid_0's l1: 0.490264\tvalid_0's binary_logloss: 0.67797\n",
      "[46]\tvalid_0's l1: 0.490051\tvalid_0's binary_logloss: 0.677627\n",
      "[47]\tvalid_0's l1: 0.489816\tvalid_0's binary_logloss: 0.677271\n",
      "[48]\tvalid_0's l1: 0.489601\tvalid_0's binary_logloss: 0.67695\n",
      "[49]\tvalid_0's l1: 0.489454\tvalid_0's binary_logloss: 0.676806\n",
      "[50]\tvalid_0's l1: 0.489185\tvalid_0's binary_logloss: 0.676426\n",
      "[51]\tvalid_0's l1: 0.489023\tvalid_0's binary_logloss: 0.676251\n",
      "[52]\tvalid_0's l1: 0.488809\tvalid_0's binary_logloss: 0.67603\n",
      "[53]\tvalid_0's l1: 0.48854\tvalid_0's binary_logloss: 0.675591\n",
      "[54]\tvalid_0's l1: 0.488333\tvalid_0's binary_logloss: 0.675407\n",
      "[55]\tvalid_0's l1: 0.488277\tvalid_0's binary_logloss: 0.675373\n",
      "[56]\tvalid_0's l1: 0.488113\tvalid_0's binary_logloss: 0.675294\n",
      "[57]\tvalid_0's l1: 0.487899\tvalid_0's binary_logloss: 0.67515\n",
      "[58]\tvalid_0's l1: 0.487749\tvalid_0's binary_logloss: 0.675151\n",
      "[59]\tvalid_0's l1: 0.487696\tvalid_0's binary_logloss: 0.675141\n",
      "[60]\tvalid_0's l1: 0.487531\tvalid_0's binary_logloss: 0.675131\n",
      "[61]\tvalid_0's l1: 0.487334\tvalid_0's binary_logloss: 0.675094\n",
      "[62]\tvalid_0's l1: 0.487244\tvalid_0's binary_logloss: 0.674955\n",
      "[63]\tvalid_0's l1: 0.487155\tvalid_0's binary_logloss: 0.674836\n",
      "[64]\tvalid_0's l1: 0.487122\tvalid_0's binary_logloss: 0.67488\n",
      "[65]\tvalid_0's l1: 0.486985\tvalid_0's binary_logloss: 0.674948\n",
      "[66]\tvalid_0's l1: 0.486898\tvalid_0's binary_logloss: 0.674846\n",
      "[67]\tvalid_0's l1: 0.48685\tvalid_0's binary_logloss: 0.674861\n",
      "[68]\tvalid_0's l1: 0.486814\tvalid_0's binary_logloss: 0.675031\n",
      "Early stopping, best iteration is:\n",
      "[63]\tvalid_0's l1: 0.487155\tvalid_0's binary_logloss: 0.674836\n",
      "[1]\tvalid_0's l1: 0.501037\tvalid_0's binary_logloss: 0.695769\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500797\tvalid_0's binary_logloss: 0.69527\n",
      "[3]\tvalid_0's l1: 0.500554\tvalid_0's binary_logloss: 0.694783\n",
      "[4]\tvalid_0's l1: 0.50048\tvalid_0's binary_logloss: 0.694633\n",
      "[5]\tvalid_0's l1: 0.500387\tvalid_0's binary_logloss: 0.694468\n",
      "[6]\tvalid_0's l1: 0.500453\tvalid_0's binary_logloss: 0.694621\n",
      "[7]\tvalid_0's l1: 0.500514\tvalid_0's binary_logloss: 0.694782\n",
      "[8]\tvalid_0's l1: 0.500457\tvalid_0's binary_logloss: 0.694724\n",
      "[9]\tvalid_0's l1: 0.500495\tvalid_0's binary_logloss: 0.694795\n",
      "[10]\tvalid_0's l1: 0.500397\tvalid_0's binary_logloss: 0.69462\n",
      "Early stopping, best iteration is:\n",
      "[5]\tvalid_0's l1: 0.500387\tvalid_0's binary_logloss: 0.694468\n",
      "[1]\tvalid_0's l1: 0.50108\tvalid_0's binary_logloss: 0.695823\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500872\tvalid_0's binary_logloss: 0.695376\n",
      "[3]\tvalid_0's l1: 0.50058\tvalid_0's binary_logloss: 0.694758\n",
      "[4]\tvalid_0's l1: 0.500335\tvalid_0's binary_logloss: 0.694294\n",
      "[5]\tvalid_0's l1: 0.500093\tvalid_0's binary_logloss: 0.69384\n",
      "[6]\tvalid_0's l1: 0.499801\tvalid_0's binary_logloss: 0.693316\n",
      "[7]\tvalid_0's l1: 0.499607\tvalid_0's binary_logloss: 0.693034\n",
      "[8]\tvalid_0's l1: 0.499328\tvalid_0's binary_logloss: 0.692587\n",
      "[9]\tvalid_0's l1: 0.49916\tvalid_0's binary_logloss: 0.692406\n",
      "[10]\tvalid_0's l1: 0.498886\tvalid_0's binary_logloss: 0.691969\n",
      "[11]\tvalid_0's l1: 0.498643\tvalid_0's binary_logloss: 0.691638\n",
      "[12]\tvalid_0's l1: 0.498311\tvalid_0's binary_logloss: 0.691128\n",
      "[13]\tvalid_0's l1: 0.497963\tvalid_0's binary_logloss: 0.690614\n",
      "[14]\tvalid_0's l1: 0.497912\tvalid_0's binary_logloss: 0.690641\n",
      "[15]\tvalid_0's l1: 0.497772\tvalid_0's binary_logloss: 0.69048\n",
      "[16]\tvalid_0's l1: 0.497748\tvalid_0's binary_logloss: 0.690591\n",
      "[17]\tvalid_0's l1: 0.497611\tvalid_0's binary_logloss: 0.690466\n",
      "[18]\tvalid_0's l1: 0.497475\tvalid_0's binary_logloss: 0.690367\n",
      "[19]\tvalid_0's l1: 0.497453\tvalid_0's binary_logloss: 0.690525\n",
      "[20]\tvalid_0's l1: 0.497402\tvalid_0's binary_logloss: 0.690599\n",
      "[21]\tvalid_0's l1: 0.497268\tvalid_0's binary_logloss: 0.690542\n",
      "[22]\tvalid_0's l1: 0.497142\tvalid_0's binary_logloss: 0.690513\n",
      "[23]\tvalid_0's l1: 0.49716\tvalid_0's binary_logloss: 0.690653\n",
      "Early stopping, best iteration is:\n",
      "[18]\tvalid_0's l1: 0.497475\tvalid_0's binary_logloss: 0.690367\n",
      "[1]\tvalid_0's l1: 0.501182\tvalid_0's binary_logloss: 0.696082\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501073\tvalid_0's binary_logloss: 0.695879\n",
      "[3]\tvalid_0's l1: 0.500988\tvalid_0's binary_logloss: 0.695703\n",
      "[4]\tvalid_0's l1: 0.500884\tvalid_0's binary_logloss: 0.695538\n",
      "[5]\tvalid_0's l1: 0.500784\tvalid_0's binary_logloss: 0.695323\n",
      "[6]\tvalid_0's l1: 0.500685\tvalid_0's binary_logloss: 0.695136\n",
      "[7]\tvalid_0's l1: 0.500591\tvalid_0's binary_logloss: 0.694986\n",
      "[8]\tvalid_0's l1: 0.500489\tvalid_0's binary_logloss: 0.694829\n",
      "[9]\tvalid_0's l1: 0.50041\tvalid_0's binary_logloss: 0.694733\n",
      "[10]\tvalid_0's l1: 0.500074\tvalid_0's binary_logloss: 0.694049\n",
      "[11]\tvalid_0's l1: 0.499963\tvalid_0's binary_logloss: 0.693916\n",
      "[12]\tvalid_0's l1: 0.499619\tvalid_0's binary_logloss: 0.693224\n",
      "[13]\tvalid_0's l1: 0.499487\tvalid_0's binary_logloss: 0.693074\n",
      "[14]\tvalid_0's l1: 0.499395\tvalid_0's binary_logloss: 0.69299\n",
      "[15]\tvalid_0's l1: 0.499178\tvalid_0's binary_logloss: 0.692686\n",
      "[16]\tvalid_0's l1: 0.498841\tvalid_0's binary_logloss: 0.692018\n",
      "[17]\tvalid_0's l1: 0.498758\tvalid_0's binary_logloss: 0.69198\n",
      "[18]\tvalid_0's l1: 0.498686\tvalid_0's binary_logloss: 0.692\n",
      "[19]\tvalid_0's l1: 0.498562\tvalid_0's binary_logloss: 0.691822\n",
      "[20]\tvalid_0's l1: 0.498373\tvalid_0's binary_logloss: 0.691624\n",
      "[21]\tvalid_0's l1: 0.498329\tvalid_0's binary_logloss: 0.691738\n",
      "[22]\tvalid_0's l1: 0.498207\tvalid_0's binary_logloss: 0.691594\n",
      "[23]\tvalid_0's l1: 0.498012\tvalid_0's binary_logloss: 0.691432\n",
      "[24]\tvalid_0's l1: 0.497893\tvalid_0's binary_logloss: 0.691317\n",
      "[25]\tvalid_0's l1: 0.497706\tvalid_0's binary_logloss: 0.691179\n",
      "[26]\tvalid_0's l1: 0.497515\tvalid_0's binary_logloss: 0.691066\n",
      "[27]\tvalid_0's l1: 0.497388\tvalid_0's binary_logloss: 0.690936\n",
      "[28]\tvalid_0's l1: 0.497212\tvalid_0's binary_logloss: 0.690849\n",
      "[29]\tvalid_0's l1: 0.497094\tvalid_0's binary_logloss: 0.690757\n",
      "[30]\tvalid_0's l1: 0.496965\tvalid_0's binary_logloss: 0.69079\n",
      "[31]\tvalid_0's l1: 0.496881\tvalid_0's binary_logloss: 0.690896\n",
      "[32]\tvalid_0's l1: 0.496776\tvalid_0's binary_logloss: 0.690881\n",
      "[33]\tvalid_0's l1: 0.496677\tvalid_0's binary_logloss: 0.690995\n",
      "[34]\tvalid_0's l1: 0.496566\tvalid_0's binary_logloss: 0.690989\n",
      "Early stopping, best iteration is:\n",
      "[29]\tvalid_0's l1: 0.497094\tvalid_0's binary_logloss: 0.690757\n",
      "[1]\tvalid_0's l1: 0.501023\tvalid_0's binary_logloss: 0.695841\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500733\tvalid_0's binary_logloss: 0.6953\n",
      "[3]\tvalid_0's l1: 0.500415\tvalid_0's binary_logloss: 0.694709\n",
      "[4]\tvalid_0's l1: 0.500148\tvalid_0's binary_logloss: 0.694267\n",
      "[5]\tvalid_0's l1: 0.499836\tvalid_0's binary_logloss: 0.69373\n",
      "[6]\tvalid_0's l1: 0.499575\tvalid_0's binary_logloss: 0.693341\n",
      "[7]\tvalid_0's l1: 0.499282\tvalid_0's binary_logloss: 0.692879\n",
      "[8]\tvalid_0's l1: 0.499094\tvalid_0's binary_logloss: 0.69265\n",
      "[9]\tvalid_0's l1: 0.498849\tvalid_0's binary_logloss: 0.69232\n",
      "[10]\tvalid_0's l1: 0.498665\tvalid_0's binary_logloss: 0.692129\n",
      "[11]\tvalid_0's l1: 0.498382\tvalid_0's binary_logloss: 0.691748\n",
      "[12]\tvalid_0's l1: 0.498012\tvalid_0's binary_logloss: 0.691198\n",
      "[13]\tvalid_0's l1: 0.497732\tvalid_0's binary_logloss: 0.690849\n",
      "[14]\tvalid_0's l1: 0.497554\tvalid_0's binary_logloss: 0.690583\n",
      "[15]\tvalid_0's l1: 0.497379\tvalid_0's binary_logloss: 0.69034\n",
      "[16]\tvalid_0's l1: 0.497218\tvalid_0's binary_logloss: 0.690146\n",
      "[17]\tvalid_0's l1: 0.497086\tvalid_0's binary_logloss: 0.690009\n",
      "[18]\tvalid_0's l1: 0.496941\tvalid_0's binary_logloss: 0.689882\n",
      "[19]\tvalid_0's l1: 0.496774\tvalid_0's binary_logloss: 0.689727\n",
      "[20]\tvalid_0's l1: 0.496632\tvalid_0's binary_logloss: 0.689641\n",
      "[21]\tvalid_0's l1: 0.496531\tvalid_0's binary_logloss: 0.689633\n",
      "[22]\tvalid_0's l1: 0.49643\tvalid_0's binary_logloss: 0.689566\n",
      "[23]\tvalid_0's l1: 0.496323\tvalid_0's binary_logloss: 0.68949\n",
      "[24]\tvalid_0's l1: 0.496004\tvalid_0's binary_logloss: 0.689148\n",
      "[25]\tvalid_0's l1: 0.495848\tvalid_0's binary_logloss: 0.689036\n",
      "[26]\tvalid_0's l1: 0.49575\tvalid_0's binary_logloss: 0.688981\n",
      "[27]\tvalid_0's l1: 0.495654\tvalid_0's binary_logloss: 0.688962\n",
      "[28]\tvalid_0's l1: 0.495601\tvalid_0's binary_logloss: 0.689001\n",
      "[29]\tvalid_0's l1: 0.4955\tvalid_0's binary_logloss: 0.688945\n",
      "[30]\tvalid_0's l1: 0.495301\tvalid_0's binary_logloss: 0.688823\n",
      "[31]\tvalid_0's l1: 0.49522\tvalid_0's binary_logloss: 0.688865\n",
      "[32]\tvalid_0's l1: 0.49511\tvalid_0's binary_logloss: 0.688851\n",
      "[33]\tvalid_0's l1: 0.494931\tvalid_0's binary_logloss: 0.688814\n",
      "[34]\tvalid_0's l1: 0.494864\tvalid_0's binary_logloss: 0.688899\n",
      "[35]\tvalid_0's l1: 0.494688\tvalid_0's binary_logloss: 0.688887\n",
      "[36]\tvalid_0's l1: 0.494644\tvalid_0's binary_logloss: 0.689028\n",
      "[37]\tvalid_0's l1: 0.494539\tvalid_0's binary_logloss: 0.689028\n",
      "[38]\tvalid_0's l1: 0.494408\tvalid_0's binary_logloss: 0.688962\n",
      "Early stopping, best iteration is:\n",
      "[33]\tvalid_0's l1: 0.494931\tvalid_0's binary_logloss: 0.688814\n",
      "[1]\tvalid_0's l1: 0.501059\tvalid_0's binary_logloss: 0.695877\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500792\tvalid_0's binary_logloss: 0.69535\n",
      "[3]\tvalid_0's l1: 0.500528\tvalid_0's binary_logloss: 0.694837\n",
      "[4]\tvalid_0's l1: 0.500165\tvalid_0's binary_logloss: 0.694078\n",
      "[5]\tvalid_0's l1: 0.499825\tvalid_0's binary_logloss: 0.693403\n",
      "[6]\tvalid_0's l1: 0.499567\tvalid_0's binary_logloss: 0.692919\n",
      "[7]\tvalid_0's l1: 0.499207\tvalid_0's binary_logloss: 0.692231\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[8]\tvalid_0's l1: 0.499002\tvalid_0's binary_logloss: 0.691876\n",
      "[9]\tvalid_0's l1: 0.498683\tvalid_0's binary_logloss: 0.691296\n",
      "[10]\tvalid_0's l1: 0.498595\tvalid_0's binary_logloss: 0.691118\n",
      "[11]\tvalid_0's l1: 0.498273\tvalid_0's binary_logloss: 0.690553\n",
      "[12]\tvalid_0's l1: 0.498075\tvalid_0's binary_logloss: 0.690227\n",
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      "[14]\tvalid_0's l1: 0.497693\tvalid_0's binary_logloss: 0.689588\n",
      "[15]\tvalid_0's l1: 0.497422\tvalid_0's binary_logloss: 0.689174\n",
      "[16]\tvalid_0's l1: 0.49723\tvalid_0's binary_logloss: 0.688876\n",
      "[17]\tvalid_0's l1: 0.496957\tvalid_0's binary_logloss: 0.688479\n",
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      "[33]\tvalid_0's l1: 0.493956\tvalid_0's binary_logloss: 0.684535\n",
      "[34]\tvalid_0's l1: 0.493776\tvalid_0's binary_logloss: 0.684263\n",
      "[35]\tvalid_0's l1: 0.493496\tvalid_0's binary_logloss: 0.683914\n",
      "[36]\tvalid_0's l1: 0.493485\tvalid_0's binary_logloss: 0.684086\n",
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      "[39]\tvalid_0's l1: 0.492852\tvalid_0's binary_logloss: 0.683125\n",
      "[40]\tvalid_0's l1: 0.492634\tvalid_0's binary_logloss: 0.682925\n",
      "[41]\tvalid_0's l1: 0.492436\tvalid_0's binary_logloss: 0.682549\n",
      "[42]\tvalid_0's l1: 0.492194\tvalid_0's binary_logloss: 0.682111\n",
      "[43]\tvalid_0's l1: 0.492\tvalid_0's binary_logloss: 0.68178\n",
      "[44]\tvalid_0's l1: 0.491842\tvalid_0's binary_logloss: 0.681609\n",
      "[45]\tvalid_0's l1: 0.491661\tvalid_0's binary_logloss: 0.681271\n",
      "[46]\tvalid_0's l1: 0.491455\tvalid_0's binary_logloss: 0.680877\n",
      "[47]\tvalid_0's l1: 0.491174\tvalid_0's binary_logloss: 0.680414\n",
      "[48]\tvalid_0's l1: 0.490943\tvalid_0's binary_logloss: 0.68006\n",
      "[49]\tvalid_0's l1: 0.490707\tvalid_0's binary_logloss: 0.679862\n",
      "[50]\tvalid_0's l1: 0.490479\tvalid_0's binary_logloss: 0.679517\n",
      "[51]\tvalid_0's l1: 0.490313\tvalid_0's binary_logloss: 0.679306\n",
      "[52]\tvalid_0's l1: 0.490208\tvalid_0's binary_logloss: 0.679196\n",
      "[53]\tvalid_0's l1: 0.489906\tvalid_0's binary_logloss: 0.678806\n",
      "[54]\tvalid_0's l1: 0.489737\tvalid_0's binary_logloss: 0.678682\n",
      "[55]\tvalid_0's l1: 0.489695\tvalid_0's binary_logloss: 0.6787\n",
      "[56]\tvalid_0's l1: 0.489399\tvalid_0's binary_logloss: 0.678369\n",
      "[57]\tvalid_0's l1: 0.489234\tvalid_0's binary_logloss: 0.678299\n",
      "[58]\tvalid_0's l1: 0.489061\tvalid_0's binary_logloss: 0.678024\n",
      "[59]\tvalid_0's l1: 0.48889\tvalid_0's binary_logloss: 0.677972\n",
      "[60]\tvalid_0's l1: 0.488852\tvalid_0's binary_logloss: 0.678014\n",
      "[61]\tvalid_0's l1: 0.488566\tvalid_0's binary_logloss: 0.677764\n",
      "[62]\tvalid_0's l1: 0.4884\tvalid_0's binary_logloss: 0.677763\n",
      "[63]\tvalid_0's l1: 0.488169\tvalid_0's binary_logloss: 0.677607\n",
      "[64]\tvalid_0's l1: 0.487942\tvalid_0's binary_logloss: 0.677213\n",
      "[65]\tvalid_0's l1: 0.487737\tvalid_0's binary_logloss: 0.677199\n",
      "[66]\tvalid_0's l1: 0.487574\tvalid_0's binary_logloss: 0.677183\n",
      "[67]\tvalid_0's l1: 0.487388\tvalid_0's binary_logloss: 0.676848\n",
      "[68]\tvalid_0's l1: 0.487145\tvalid_0's binary_logloss: 0.67667\n",
      "[69]\tvalid_0's l1: 0.486931\tvalid_0's binary_logloss: 0.676461\n",
      "[70]\tvalid_0's l1: 0.486716\tvalid_0's binary_logloss: 0.676247\n",
      "[71]\tvalid_0's l1: 0.486564\tvalid_0's binary_logloss: 0.676086\n",
      "[72]\tvalid_0's l1: 0.486293\tvalid_0's binary_logloss: 0.675568\n",
      "[73]\tvalid_0's l1: 0.486089\tvalid_0's binary_logloss: 0.675237\n",
      "[74]\tvalid_0's l1: 0.486112\tvalid_0's binary_logloss: 0.675499\n",
      "[75]\tvalid_0's l1: 0.485844\tvalid_0's binary_logloss: 0.674997\n",
      "[76]\tvalid_0's l1: 0.485809\tvalid_0's binary_logloss: 0.675179\n",
      "[77]\tvalid_0's l1: 0.485813\tvalid_0's binary_logloss: 0.675434\n",
      "[78]\tvalid_0's l1: 0.485793\tvalid_0's binary_logloss: 0.675519\n",
      "[79]\tvalid_0's l1: 0.485586\tvalid_0's binary_logloss: 0.675146\n",
      "[80]\tvalid_0's l1: 0.485529\tvalid_0's binary_logloss: 0.675303\n",
      "Early stopping, best iteration is:\n",
      "[75]\tvalid_0's l1: 0.485844\tvalid_0's binary_logloss: 0.674997\n",
      "[1]\tvalid_0's l1: 0.501037\tvalid_0's binary_logloss: 0.695769\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500797\tvalid_0's binary_logloss: 0.69527\n",
      "[3]\tvalid_0's l1: 0.500554\tvalid_0's binary_logloss: 0.694783\n",
      "[4]\tvalid_0's l1: 0.50048\tvalid_0's binary_logloss: 0.694633\n",
      "[5]\tvalid_0's l1: 0.500387\tvalid_0's binary_logloss: 0.694468\n",
      "[6]\tvalid_0's l1: 0.500453\tvalid_0's binary_logloss: 0.694621\n",
      "[7]\tvalid_0's l1: 0.500514\tvalid_0's binary_logloss: 0.694782\n",
      "[8]\tvalid_0's l1: 0.500457\tvalid_0's binary_logloss: 0.694724\n",
      "[9]\tvalid_0's l1: 0.500507\tvalid_0's binary_logloss: 0.694816\n",
      "[10]\tvalid_0's l1: 0.500413\tvalid_0's binary_logloss: 0.694642\n",
      "Early stopping, best iteration is:\n",
      "[5]\tvalid_0's l1: 0.500387\tvalid_0's binary_logloss: 0.694468\n",
      "[1]\tvalid_0's l1: 0.50108\tvalid_0's binary_logloss: 0.695823\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500872\tvalid_0's binary_logloss: 0.695376\n",
      "[3]\tvalid_0's l1: 0.50058\tvalid_0's binary_logloss: 0.694758\n",
      "[4]\tvalid_0's l1: 0.500335\tvalid_0's binary_logloss: 0.694294\n",
      "[5]\tvalid_0's l1: 0.500093\tvalid_0's binary_logloss: 0.69384\n",
      "[6]\tvalid_0's l1: 0.499801\tvalid_0's binary_logloss: 0.693316\n",
      "[7]\tvalid_0's l1: 0.499607\tvalid_0's binary_logloss: 0.693034\n",
      "[8]\tvalid_0's l1: 0.499328\tvalid_0's binary_logloss: 0.692587\n",
      "[9]\tvalid_0's l1: 0.49916\tvalid_0's binary_logloss: 0.692406\n",
      "[10]\tvalid_0's l1: 0.498886\tvalid_0's binary_logloss: 0.691969\n",
      "[11]\tvalid_0's l1: 0.498666\tvalid_0's binary_logloss: 0.691683\n",
      "[12]\tvalid_0's l1: 0.49836\tvalid_0's binary_logloss: 0.691218\n",
      "[13]\tvalid_0's l1: 0.498014\tvalid_0's binary_logloss: 0.690696\n",
      "[14]\tvalid_0's l1: 0.497963\tvalid_0's binary_logloss: 0.690723\n",
      "[15]\tvalid_0's l1: 0.497823\tvalid_0's binary_logloss: 0.690562\n",
      "[16]\tvalid_0's l1: 0.497799\tvalid_0's binary_logloss: 0.690672\n",
      "[17]\tvalid_0's l1: 0.497662\tvalid_0's binary_logloss: 0.690546\n",
      "[18]\tvalid_0's l1: 0.49764\tvalid_0's binary_logloss: 0.690689\n",
      "[19]\tvalid_0's l1: 0.497504\tvalid_0's binary_logloss: 0.690605\n",
      "[20]\tvalid_0's l1: 0.497488\tvalid_0's binary_logloss: 0.690745\n",
      "[21]\tvalid_0's l1: 0.497355\tvalid_0's binary_logloss: 0.690686\n",
      "[22]\tvalid_0's l1: 0.497228\tvalid_0's binary_logloss: 0.690657\n",
      "Early stopping, best iteration is:\n",
      "[17]\tvalid_0's l1: 0.497662\tvalid_0's binary_logloss: 0.690546\n",
      "[1]\tvalid_0's l1: 0.501182\tvalid_0's binary_logloss: 0.696082\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501073\tvalid_0's binary_logloss: 0.695876\n",
      "[3]\tvalid_0's l1: 0.500996\tvalid_0's binary_logloss: 0.695717\n",
      "[4]\tvalid_0's l1: 0.500898\tvalid_0's binary_logloss: 0.695563\n",
      "[5]\tvalid_0's l1: 0.500798\tvalid_0's binary_logloss: 0.695349\n",
      "[6]\tvalid_0's l1: 0.500698\tvalid_0's binary_logloss: 0.695162\n",
      "[7]\tvalid_0's l1: 0.500605\tvalid_0's binary_logloss: 0.695011\n",
      "[8]\tvalid_0's l1: 0.500508\tvalid_0's binary_logloss: 0.694866\n",
      "[9]\tvalid_0's l1: 0.500424\tvalid_0's binary_logloss: 0.694759\n",
      "[10]\tvalid_0's l1: 0.500087\tvalid_0's binary_logloss: 0.694075\n",
      "[11]\tvalid_0's l1: 0.499977\tvalid_0's binary_logloss: 0.693942\n",
      "[12]\tvalid_0's l1: 0.499633\tvalid_0's binary_logloss: 0.693251\n",
      "[13]\tvalid_0's l1: 0.499501\tvalid_0's binary_logloss: 0.693101\n",
      "[14]\tvalid_0's l1: 0.499409\tvalid_0's binary_logloss: 0.693017\n",
      "[15]\tvalid_0's l1: 0.499192\tvalid_0's binary_logloss: 0.692713\n",
      "[16]\tvalid_0's l1: 0.498855\tvalid_0's binary_logloss: 0.692045\n",
      "[17]\tvalid_0's l1: 0.498766\tvalid_0's binary_logloss: 0.691996\n",
      "[18]\tvalid_0's l1: 0.498695\tvalid_0's binary_logloss: 0.692016\n",
      "[19]\tvalid_0's l1: 0.49857\tvalid_0's binary_logloss: 0.691837\n",
      "[20]\tvalid_0's l1: 0.498381\tvalid_0's binary_logloss: 0.691639\n",
      "[21]\tvalid_0's l1: 0.498265\tvalid_0's binary_logloss: 0.691607\n",
      "[22]\tvalid_0's l1: 0.498144\tvalid_0's binary_logloss: 0.691464\n",
      "[23]\tvalid_0's l1: 0.497901\tvalid_0's binary_logloss: 0.691201\n",
      "[24]\tvalid_0's l1: 0.497771\tvalid_0's binary_logloss: 0.691046\n",
      "[25]\tvalid_0's l1: 0.497702\tvalid_0's binary_logloss: 0.691148\n",
      "[26]\tvalid_0's l1: 0.497512\tvalid_0's binary_logloss: 0.691032\n",
      "[27]\tvalid_0's l1: 0.497395\tvalid_0's binary_logloss: 0.69095\n",
      "[28]\tvalid_0's l1: 0.497219\tvalid_0's binary_logloss: 0.690863\n",
      "[29]\tvalid_0's l1: 0.497035\tvalid_0's binary_logloss: 0.690812\n",
      "[30]\tvalid_0's l1: 0.496927\tvalid_0's binary_logloss: 0.690773\n",
      "[31]\tvalid_0's l1: 0.496906\tvalid_0's binary_logloss: 0.690997\n",
      "[32]\tvalid_0's l1: 0.496801\tvalid_0's binary_logloss: 0.690981\n",
      "[33]\tvalid_0's l1: 0.496752\tvalid_0's binary_logloss: 0.691188\n",
      "[34]\tvalid_0's l1: 0.496642\tvalid_0's binary_logloss: 0.691183\n",
      "[35]\tvalid_0's l1: 0.496498\tvalid_0's binary_logloss: 0.691208\n",
      "Early stopping, best iteration is:\n",
      "[30]\tvalid_0's l1: 0.496927\tvalid_0's binary_logloss: 0.690773\n",
      "[1]\tvalid_0's l1: 0.501\tvalid_0's binary_logloss: 0.695793\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500688\tvalid_0's binary_logloss: 0.695206\n",
      "[3]\tvalid_0's l1: 0.500347\tvalid_0's binary_logloss: 0.694573\n",
      "[4]\tvalid_0's l1: 0.500059\tvalid_0's binary_logloss: 0.694089\n",
      "[5]\tvalid_0's l1: 0.499725\tvalid_0's binary_logloss: 0.693513\n",
      "[6]\tvalid_0's l1: 0.49944\tvalid_0's binary_logloss: 0.693082\n",
      "[7]\tvalid_0's l1: 0.499152\tvalid_0's binary_logloss: 0.692649\n",
      "[8]\tvalid_0's l1: 0.498924\tvalid_0's binary_logloss: 0.69235\n",
      "[9]\tvalid_0's l1: 0.498724\tvalid_0's binary_logloss: 0.69209\n",
      "[10]\tvalid_0's l1: 0.498351\tvalid_0's binary_logloss: 0.691533\n",
      "[11]\tvalid_0's l1: 0.498196\tvalid_0's binary_logloss: 0.691399\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[12]\tvalid_0's l1: 0.497905\tvalid_0's binary_logloss: 0.691039\n",
      "[13]\tvalid_0's l1: 0.497565\tvalid_0's binary_logloss: 0.690567\n",
      "[14]\tvalid_0's l1: 0.497219\tvalid_0's binary_logloss: 0.690101\n",
      "[15]\tvalid_0's l1: 0.497032\tvalid_0's binary_logloss: 0.689824\n",
      "[16]\tvalid_0's l1: 0.496848\tvalid_0's binary_logloss: 0.689571\n",
      "[17]\tvalid_0's l1: 0.496676\tvalid_0's binary_logloss: 0.689362\n",
      "[18]\tvalid_0's l1: 0.496531\tvalid_0's binary_logloss: 0.689223\n",
      "[19]\tvalid_0's l1: 0.496394\tvalid_0's binary_logloss: 0.689099\n",
      "[20]\tvalid_0's l1: 0.496265\tvalid_0's binary_logloss: 0.689025\n",
      "[21]\tvalid_0's l1: 0.496078\tvalid_0's binary_logloss: 0.688857\n",
      "[22]\tvalid_0's l1: 0.495983\tvalid_0's binary_logloss: 0.688867\n",
      "[23]\tvalid_0's l1: 0.495806\tvalid_0's binary_logloss: 0.688751\n",
      "[24]\tvalid_0's l1: 0.49568\tvalid_0's binary_logloss: 0.688658\n",
      "[25]\tvalid_0's l1: 0.495549\tvalid_0's binary_logloss: 0.688514\n",
      "[26]\tvalid_0's l1: 0.495437\tvalid_0's binary_logloss: 0.688464\n",
      "[27]\tvalid_0's l1: 0.495361\tvalid_0's binary_logloss: 0.68854\n",
      "[28]\tvalid_0's l1: 0.495321\tvalid_0's binary_logloss: 0.688585\n",
      "[29]\tvalid_0's l1: 0.495207\tvalid_0's binary_logloss: 0.6885\n",
      "[30]\tvalid_0's l1: 0.495077\tvalid_0's binary_logloss: 0.688437\n",
      "[31]\tvalid_0's l1: 0.494997\tvalid_0's binary_logloss: 0.688482\n",
      "[32]\tvalid_0's l1: 0.494938\tvalid_0's binary_logloss: 0.688596\n",
      "[33]\tvalid_0's l1: 0.494759\tvalid_0's binary_logloss: 0.688554\n",
      "[34]\tvalid_0's l1: 0.494662\tvalid_0's binary_logloss: 0.688536\n",
      "[35]\tvalid_0's l1: 0.494537\tvalid_0's binary_logloss: 0.688529\n",
      "Early stopping, best iteration is:\n",
      "[30]\tvalid_0's l1: 0.495077\tvalid_0's binary_logloss: 0.688437\n",
      "[1]\tvalid_0's l1: 0.501059\tvalid_0's binary_logloss: 0.695877\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500792\tvalid_0's binary_logloss: 0.69535\n",
      "[3]\tvalid_0's l1: 0.500528\tvalid_0's binary_logloss: 0.694837\n",
      "[4]\tvalid_0's l1: 0.500132\tvalid_0's binary_logloss: 0.694018\n",
      "[5]\tvalid_0's l1: 0.499714\tvalid_0's binary_logloss: 0.693199\n",
      "[6]\tvalid_0's l1: 0.499456\tvalid_0's binary_logloss: 0.692716\n",
      "[7]\tvalid_0's l1: 0.499033\tvalid_0's binary_logloss: 0.691912\n",
      "[8]\tvalid_0's l1: 0.498829\tvalid_0's binary_logloss: 0.691559\n",
      "[9]\tvalid_0's l1: 0.498469\tvalid_0's binary_logloss: 0.690902\n",
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      "[12]\tvalid_0's l1: 0.497839\tvalid_0's binary_logloss: 0.689741\n",
      "[13]\tvalid_0's l1: 0.497524\tvalid_0's binary_logloss: 0.689216\n",
      "[14]\tvalid_0's l1: 0.49733\tvalid_0's binary_logloss: 0.688906\n",
      "[15]\tvalid_0's l1: 0.496991\tvalid_0's binary_logloss: 0.68835\n",
      "[16]\tvalid_0's l1: 0.496811\tvalid_0's binary_logloss: 0.688019\n",
      "[17]\tvalid_0's l1: 0.496534\tvalid_0's binary_logloss: 0.68759\n",
      "[18]\tvalid_0's l1: 0.496316\tvalid_0's binary_logloss: 0.687135\n",
      "[19]\tvalid_0's l1: 0.495956\tvalid_0's binary_logloss: 0.686441\n",
      "[20]\tvalid_0's l1: 0.495617\tvalid_0's binary_logloss: 0.685924\n",
      "[21]\tvalid_0's l1: 0.495319\tvalid_0's binary_logloss: 0.6855\n",
      "[22]\tvalid_0's l1: 0.495132\tvalid_0's binary_logloss: 0.685178\n",
      "[23]\tvalid_0's l1: 0.494789\tvalid_0's binary_logloss: 0.684686\n",
      "[24]\tvalid_0's l1: 0.49456\tvalid_0's binary_logloss: 0.684245\n",
      "[25]\tvalid_0's l1: 0.494355\tvalid_0's binary_logloss: 0.683899\n",
      "[26]\tvalid_0's l1: 0.494248\tvalid_0's binary_logloss: 0.683756\n",
      "[27]\tvalid_0's l1: 0.493961\tvalid_0's binary_logloss: 0.683359\n",
      "[28]\tvalid_0's l1: 0.493782\tvalid_0's binary_logloss: 0.683073\n",
      "[29]\tvalid_0's l1: 0.493458\tvalid_0's binary_logloss: 0.682659\n",
      "[30]\tvalid_0's l1: 0.493296\tvalid_0's binary_logloss: 0.682451\n",
      "[31]\tvalid_0's l1: 0.493025\tvalid_0's binary_logloss: 0.6821\n",
      "[32]\tvalid_0's l1: 0.492859\tvalid_0's binary_logloss: 0.681884\n",
      "[33]\tvalid_0's l1: 0.492671\tvalid_0's binary_logloss: 0.681616\n",
      "[34]\tvalid_0's l1: 0.492521\tvalid_0's binary_logloss: 0.681326\n",
      "[35]\tvalid_0's l1: 0.492325\tvalid_0's binary_logloss: 0.681099\n",
      "[36]\tvalid_0's l1: 0.492141\tvalid_0's binary_logloss: 0.68084\n",
      "[37]\tvalid_0's l1: 0.491978\tvalid_0's binary_logloss: 0.68064\n",
      "[38]\tvalid_0's l1: 0.491689\tvalid_0's binary_logloss: 0.680165\n",
      "[39]\tvalid_0's l1: 0.49164\tvalid_0's binary_logloss: 0.680163\n",
      "[40]\tvalid_0's l1: 0.491473\tvalid_0's binary_logloss: 0.679946\n",
      "[41]\tvalid_0's l1: 0.491229\tvalid_0's binary_logloss: 0.679497\n",
      "[42]\tvalid_0's l1: 0.490988\tvalid_0's binary_logloss: 0.679073\n",
      "[43]\tvalid_0's l1: 0.490776\tvalid_0's binary_logloss: 0.678708\n",
      "[44]\tvalid_0's l1: 0.490418\tvalid_0's binary_logloss: 0.678144\n",
      "[45]\tvalid_0's l1: 0.490264\tvalid_0's binary_logloss: 0.67797\n",
      "[46]\tvalid_0's l1: 0.490051\tvalid_0's binary_logloss: 0.677627\n",
      "[47]\tvalid_0's l1: 0.489816\tvalid_0's binary_logloss: 0.677271\n",
      "[48]\tvalid_0's l1: 0.489601\tvalid_0's binary_logloss: 0.67695\n",
      "[49]\tvalid_0's l1: 0.489454\tvalid_0's binary_logloss: 0.676806\n",
      "[50]\tvalid_0's l1: 0.489185\tvalid_0's binary_logloss: 0.676426\n",
      "[51]\tvalid_0's l1: 0.489023\tvalid_0's binary_logloss: 0.676251\n",
      "[52]\tvalid_0's l1: 0.488809\tvalid_0's binary_logloss: 0.67603\n",
      "[53]\tvalid_0's l1: 0.48854\tvalid_0's binary_logloss: 0.675591\n",
      "[54]\tvalid_0's l1: 0.488333\tvalid_0's binary_logloss: 0.675407\n",
      "[55]\tvalid_0's l1: 0.488277\tvalid_0's binary_logloss: 0.675373\n",
      "[56]\tvalid_0's l1: 0.488113\tvalid_0's binary_logloss: 0.675294\n",
      "[57]\tvalid_0's l1: 0.487899\tvalid_0's binary_logloss: 0.67515\n",
      "[58]\tvalid_0's l1: 0.487749\tvalid_0's binary_logloss: 0.675151\n",
      "[59]\tvalid_0's l1: 0.487696\tvalid_0's binary_logloss: 0.675141\n",
      "[60]\tvalid_0's l1: 0.487531\tvalid_0's binary_logloss: 0.675131\n",
      "[61]\tvalid_0's l1: 0.487334\tvalid_0's binary_logloss: 0.675094\n",
      "[62]\tvalid_0's l1: 0.487244\tvalid_0's binary_logloss: 0.674955\n",
      "[63]\tvalid_0's l1: 0.487155\tvalid_0's binary_logloss: 0.674836\n",
      "[64]\tvalid_0's l1: 0.487122\tvalid_0's binary_logloss: 0.67488\n",
      "[65]\tvalid_0's l1: 0.486985\tvalid_0's binary_logloss: 0.674948\n",
      "[66]\tvalid_0's l1: 0.486898\tvalid_0's binary_logloss: 0.674846\n",
      "[67]\tvalid_0's l1: 0.48685\tvalid_0's binary_logloss: 0.674861\n",
      "[68]\tvalid_0's l1: 0.486814\tvalid_0's binary_logloss: 0.675031\n",
      "Early stopping, best iteration is:\n",
      "[63]\tvalid_0's l1: 0.487155\tvalid_0's binary_logloss: 0.674836\n",
      "[1]\tvalid_0's l1: 0.501037\tvalid_0's binary_logloss: 0.695769\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500797\tvalid_0's binary_logloss: 0.69527\n",
      "[3]\tvalid_0's l1: 0.500554\tvalid_0's binary_logloss: 0.694783\n",
      "[4]\tvalid_0's l1: 0.50048\tvalid_0's binary_logloss: 0.694633\n",
      "[5]\tvalid_0's l1: 0.500387\tvalid_0's binary_logloss: 0.694468\n",
      "[6]\tvalid_0's l1: 0.500453\tvalid_0's binary_logloss: 0.694621\n",
      "[7]\tvalid_0's l1: 0.500514\tvalid_0's binary_logloss: 0.694782\n",
      "[8]\tvalid_0's l1: 0.500457\tvalid_0's binary_logloss: 0.694724\n",
      "[9]\tvalid_0's l1: 0.500495\tvalid_0's binary_logloss: 0.694795\n",
      "[10]\tvalid_0's l1: 0.500397\tvalid_0's binary_logloss: 0.69462\n",
      "Early stopping, best iteration is:\n",
      "[5]\tvalid_0's l1: 0.500387\tvalid_0's binary_logloss: 0.694468\n",
      "[1]\tvalid_0's l1: 0.50108\tvalid_0's binary_logloss: 0.695823\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500872\tvalid_0's binary_logloss: 0.695376\n",
      "[3]\tvalid_0's l1: 0.50058\tvalid_0's binary_logloss: 0.694758\n",
      "[4]\tvalid_0's l1: 0.500335\tvalid_0's binary_logloss: 0.694294\n",
      "[5]\tvalid_0's l1: 0.500093\tvalid_0's binary_logloss: 0.69384\n",
      "[6]\tvalid_0's l1: 0.499801\tvalid_0's binary_logloss: 0.693316\n",
      "[7]\tvalid_0's l1: 0.499607\tvalid_0's binary_logloss: 0.693034\n",
      "[8]\tvalid_0's l1: 0.499328\tvalid_0's binary_logloss: 0.692587\n",
      "[9]\tvalid_0's l1: 0.49916\tvalid_0's binary_logloss: 0.692406\n",
      "[10]\tvalid_0's l1: 0.498886\tvalid_0's binary_logloss: 0.691969\n",
      "[11]\tvalid_0's l1: 0.498643\tvalid_0's binary_logloss: 0.691638\n",
      "[12]\tvalid_0's l1: 0.498311\tvalid_0's binary_logloss: 0.691128\n",
      "[13]\tvalid_0's l1: 0.497963\tvalid_0's binary_logloss: 0.690614\n",
      "[14]\tvalid_0's l1: 0.497912\tvalid_0's binary_logloss: 0.690641\n",
      "[15]\tvalid_0's l1: 0.497772\tvalid_0's binary_logloss: 0.69048\n",
      "[16]\tvalid_0's l1: 0.497748\tvalid_0's binary_logloss: 0.690591\n",
      "[17]\tvalid_0's l1: 0.497611\tvalid_0's binary_logloss: 0.690466\n",
      "[18]\tvalid_0's l1: 0.497475\tvalid_0's binary_logloss: 0.690367\n",
      "[19]\tvalid_0's l1: 0.497453\tvalid_0's binary_logloss: 0.690525\n",
      "[20]\tvalid_0's l1: 0.497402\tvalid_0's binary_logloss: 0.690599\n",
      "[21]\tvalid_0's l1: 0.497268\tvalid_0's binary_logloss: 0.690542\n",
      "[22]\tvalid_0's l1: 0.497142\tvalid_0's binary_logloss: 0.690513\n",
      "[23]\tvalid_0's l1: 0.49716\tvalid_0's binary_logloss: 0.690653\n",
      "Early stopping, best iteration is:\n",
      "[18]\tvalid_0's l1: 0.497475\tvalid_0's binary_logloss: 0.690367\n",
      "[1]\tvalid_0's l1: 0.501182\tvalid_0's binary_logloss: 0.696082\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501073\tvalid_0's binary_logloss: 0.695876\n",
      "[3]\tvalid_0's l1: 0.500996\tvalid_0's binary_logloss: 0.695717\n",
      "[4]\tvalid_0's l1: 0.500898\tvalid_0's binary_logloss: 0.695563\n",
      "[5]\tvalid_0's l1: 0.500798\tvalid_0's binary_logloss: 0.695349\n",
      "[6]\tvalid_0's l1: 0.500698\tvalid_0's binary_logloss: 0.695162\n",
      "[7]\tvalid_0's l1: 0.500605\tvalid_0's binary_logloss: 0.695011\n",
      "[8]\tvalid_0's l1: 0.500508\tvalid_0's binary_logloss: 0.694866\n",
      "[9]\tvalid_0's l1: 0.500424\tvalid_0's binary_logloss: 0.694759\n",
      "[10]\tvalid_0's l1: 0.500087\tvalid_0's binary_logloss: 0.694075\n",
      "[11]\tvalid_0's l1: 0.499977\tvalid_0's binary_logloss: 0.693942\n",
      "[12]\tvalid_0's l1: 0.499633\tvalid_0's binary_logloss: 0.693251\n",
      "[13]\tvalid_0's l1: 0.499501\tvalid_0's binary_logloss: 0.693101\n",
      "[14]\tvalid_0's l1: 0.499409\tvalid_0's binary_logloss: 0.693017\n",
      "[15]\tvalid_0's l1: 0.499192\tvalid_0's binary_logloss: 0.692713\n",
      "[16]\tvalid_0's l1: 0.498855\tvalid_0's binary_logloss: 0.692045\n",
      "[17]\tvalid_0's l1: 0.498766\tvalid_0's binary_logloss: 0.691996\n",
      "[18]\tvalid_0's l1: 0.498695\tvalid_0's binary_logloss: 0.692016\n",
      "[19]\tvalid_0's l1: 0.49857\tvalid_0's binary_logloss: 0.691837\n",
      "[20]\tvalid_0's l1: 0.498381\tvalid_0's binary_logloss: 0.691639\n",
      "[21]\tvalid_0's l1: 0.498265\tvalid_0's binary_logloss: 0.691607\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[22]\tvalid_0's l1: 0.498144\tvalid_0's binary_logloss: 0.691464\n",
      "[23]\tvalid_0's l1: 0.497901\tvalid_0's binary_logloss: 0.691201\n",
      "[24]\tvalid_0's l1: 0.497771\tvalid_0's binary_logloss: 0.691046\n",
      "[25]\tvalid_0's l1: 0.497702\tvalid_0's binary_logloss: 0.691148\n",
      "[26]\tvalid_0's l1: 0.497512\tvalid_0's binary_logloss: 0.691032\n",
      "[27]\tvalid_0's l1: 0.497395\tvalid_0's binary_logloss: 0.69095\n",
      "[28]\tvalid_0's l1: 0.497219\tvalid_0's binary_logloss: 0.690863\n",
      "[29]\tvalid_0's l1: 0.497035\tvalid_0's binary_logloss: 0.690812\n",
      "[30]\tvalid_0's l1: 0.496927\tvalid_0's binary_logloss: 0.690773\n",
      "[31]\tvalid_0's l1: 0.496906\tvalid_0's binary_logloss: 0.690997\n",
      "[32]\tvalid_0's l1: 0.496801\tvalid_0's binary_logloss: 0.690981\n",
      "[33]\tvalid_0's l1: 0.496752\tvalid_0's binary_logloss: 0.691188\n",
      "[34]\tvalid_0's l1: 0.496642\tvalid_0's binary_logloss: 0.691183\n",
      "[35]\tvalid_0's l1: 0.496498\tvalid_0's binary_logloss: 0.691208\n",
      "Early stopping, best iteration is:\n",
      "[30]\tvalid_0's l1: 0.496927\tvalid_0's binary_logloss: 0.690773\n",
      "[1]\tvalid_0's l1: 0.501\tvalid_0's binary_logloss: 0.695793\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500688\tvalid_0's binary_logloss: 0.695206\n",
      "[3]\tvalid_0's l1: 0.500347\tvalid_0's binary_logloss: 0.694573\n",
      "[4]\tvalid_0's l1: 0.500059\tvalid_0's binary_logloss: 0.694089\n",
      "[5]\tvalid_0's l1: 0.499725\tvalid_0's binary_logloss: 0.693513\n",
      "[6]\tvalid_0's l1: 0.49944\tvalid_0's binary_logloss: 0.693082\n",
      "[7]\tvalid_0's l1: 0.499152\tvalid_0's binary_logloss: 0.692649\n",
      "[8]\tvalid_0's l1: 0.498924\tvalid_0's binary_logloss: 0.69235\n",
      "[9]\tvalid_0's l1: 0.498724\tvalid_0's binary_logloss: 0.69209\n",
      "[10]\tvalid_0's l1: 0.498351\tvalid_0's binary_logloss: 0.691533\n",
      "[11]\tvalid_0's l1: 0.498196\tvalid_0's binary_logloss: 0.691399\n",
      "[12]\tvalid_0's l1: 0.497905\tvalid_0's binary_logloss: 0.691039\n",
      "[13]\tvalid_0's l1: 0.497565\tvalid_0's binary_logloss: 0.690567\n",
      "[14]\tvalid_0's l1: 0.497219\tvalid_0's binary_logloss: 0.690101\n",
      "[15]\tvalid_0's l1: 0.497032\tvalid_0's binary_logloss: 0.689824\n",
      "[16]\tvalid_0's l1: 0.496848\tvalid_0's binary_logloss: 0.689571\n",
      "[17]\tvalid_0's l1: 0.496676\tvalid_0's binary_logloss: 0.689362\n",
      "[18]\tvalid_0's l1: 0.496531\tvalid_0's binary_logloss: 0.689223\n",
      "[19]\tvalid_0's l1: 0.496394\tvalid_0's binary_logloss: 0.689099\n",
      "[20]\tvalid_0's l1: 0.496265\tvalid_0's binary_logloss: 0.689025\n",
      "[21]\tvalid_0's l1: 0.496078\tvalid_0's binary_logloss: 0.688857\n",
      "[22]\tvalid_0's l1: 0.495983\tvalid_0's binary_logloss: 0.688867\n",
      "[23]\tvalid_0's l1: 0.495806\tvalid_0's binary_logloss: 0.688751\n",
      "[24]\tvalid_0's l1: 0.49568\tvalid_0's binary_logloss: 0.688658\n",
      "[25]\tvalid_0's l1: 0.495549\tvalid_0's binary_logloss: 0.688514\n",
      "[26]\tvalid_0's l1: 0.495437\tvalid_0's binary_logloss: 0.688464\n",
      "[27]\tvalid_0's l1: 0.495361\tvalid_0's binary_logloss: 0.68854\n",
      "[28]\tvalid_0's l1: 0.495321\tvalid_0's binary_logloss: 0.688585\n",
      "[29]\tvalid_0's l1: 0.495207\tvalid_0's binary_logloss: 0.6885\n",
      "[30]\tvalid_0's l1: 0.495077\tvalid_0's binary_logloss: 0.688437\n",
      "[31]\tvalid_0's l1: 0.494997\tvalid_0's binary_logloss: 0.688482\n",
      "[32]\tvalid_0's l1: 0.494938\tvalid_0's binary_logloss: 0.688596\n",
      "[33]\tvalid_0's l1: 0.494759\tvalid_0's binary_logloss: 0.688554\n",
      "[34]\tvalid_0's l1: 0.494662\tvalid_0's binary_logloss: 0.688536\n",
      "[35]\tvalid_0's l1: 0.494537\tvalid_0's binary_logloss: 0.688529\n",
      "Early stopping, best iteration is:\n",
      "[30]\tvalid_0's l1: 0.495077\tvalid_0's binary_logloss: 0.688437\n",
      "[1]\tvalid_0's l1: 0.501059\tvalid_0's binary_logloss: 0.695877\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500792\tvalid_0's binary_logloss: 0.69535\n",
      "[3]\tvalid_0's l1: 0.500528\tvalid_0's binary_logloss: 0.694837\n",
      "[4]\tvalid_0's l1: 0.500132\tvalid_0's binary_logloss: 0.694018\n",
      "[5]\tvalid_0's l1: 0.499714\tvalid_0's binary_logloss: 0.693199\n",
      "[6]\tvalid_0's l1: 0.499456\tvalid_0's binary_logloss: 0.692716\n",
      "[7]\tvalid_0's l1: 0.499033\tvalid_0's binary_logloss: 0.691912\n",
      "[8]\tvalid_0's l1: 0.498829\tvalid_0's binary_logloss: 0.691559\n",
      "[9]\tvalid_0's l1: 0.498469\tvalid_0's binary_logloss: 0.690902\n",
      "[10]\tvalid_0's l1: 0.498382\tvalid_0's binary_logloss: 0.690723\n",
      "[11]\tvalid_0's l1: 0.498012\tvalid_0's binary_logloss: 0.690066\n",
      "[12]\tvalid_0's l1: 0.497839\tvalid_0's binary_logloss: 0.689741\n",
      "[13]\tvalid_0's l1: 0.497524\tvalid_0's binary_logloss: 0.689216\n",
      "[14]\tvalid_0's l1: 0.49733\tvalid_0's binary_logloss: 0.688906\n",
      "[15]\tvalid_0's l1: 0.496991\tvalid_0's binary_logloss: 0.68835\n",
      "[16]\tvalid_0's l1: 0.496811\tvalid_0's binary_logloss: 0.688019\n",
      "[17]\tvalid_0's l1: 0.496534\tvalid_0's binary_logloss: 0.68759\n",
      "[18]\tvalid_0's l1: 0.496316\tvalid_0's binary_logloss: 0.687135\n",
      "[19]\tvalid_0's l1: 0.495956\tvalid_0's binary_logloss: 0.686441\n",
      "[20]\tvalid_0's l1: 0.495617\tvalid_0's binary_logloss: 0.685924\n",
      "[21]\tvalid_0's l1: 0.495319\tvalid_0's binary_logloss: 0.6855\n",
      "[22]\tvalid_0's l1: 0.495132\tvalid_0's binary_logloss: 0.685178\n",
      "[23]\tvalid_0's l1: 0.494789\tvalid_0's binary_logloss: 0.684686\n",
      "[24]\tvalid_0's l1: 0.49456\tvalid_0's binary_logloss: 0.684245\n",
      "[25]\tvalid_0's l1: 0.494355\tvalid_0's binary_logloss: 0.683899\n",
      "[26]\tvalid_0's l1: 0.494248\tvalid_0's binary_logloss: 0.683756\n",
      "[27]\tvalid_0's l1: 0.493961\tvalid_0's binary_logloss: 0.683359\n",
      "[28]\tvalid_0's l1: 0.493782\tvalid_0's binary_logloss: 0.683073\n",
      "[29]\tvalid_0's l1: 0.493458\tvalid_0's binary_logloss: 0.682659\n",
      "[30]\tvalid_0's l1: 0.493296\tvalid_0's binary_logloss: 0.682451\n",
      "[31]\tvalid_0's l1: 0.493025\tvalid_0's binary_logloss: 0.6821\n",
      "[32]\tvalid_0's l1: 0.492859\tvalid_0's binary_logloss: 0.681884\n",
      "[33]\tvalid_0's l1: 0.492671\tvalid_0's binary_logloss: 0.681616\n",
      "[34]\tvalid_0's l1: 0.492521\tvalid_0's binary_logloss: 0.681326\n",
      "[35]\tvalid_0's l1: 0.492325\tvalid_0's binary_logloss: 0.681099\n",
      "[36]\tvalid_0's l1: 0.492141\tvalid_0's binary_logloss: 0.68084\n",
      "[37]\tvalid_0's l1: 0.491978\tvalid_0's binary_logloss: 0.68064\n",
      "[38]\tvalid_0's l1: 0.491689\tvalid_0's binary_logloss: 0.680165\n",
      "[39]\tvalid_0's l1: 0.49164\tvalid_0's binary_logloss: 0.680163\n",
      "[40]\tvalid_0's l1: 0.491473\tvalid_0's binary_logloss: 0.679946\n",
      "[41]\tvalid_0's l1: 0.491229\tvalid_0's binary_logloss: 0.679497\n",
      "[42]\tvalid_0's l1: 0.490988\tvalid_0's binary_logloss: 0.679073\n",
      "[43]\tvalid_0's l1: 0.490776\tvalid_0's binary_logloss: 0.678708\n",
      "[44]\tvalid_0's l1: 0.490418\tvalid_0's binary_logloss: 0.678144\n",
      "[45]\tvalid_0's l1: 0.490264\tvalid_0's binary_logloss: 0.67797\n",
      "[46]\tvalid_0's l1: 0.490051\tvalid_0's binary_logloss: 0.677627\n",
      "[47]\tvalid_0's l1: 0.489816\tvalid_0's binary_logloss: 0.677271\n",
      "[48]\tvalid_0's l1: 0.489601\tvalid_0's binary_logloss: 0.67695\n",
      "[49]\tvalid_0's l1: 0.489454\tvalid_0's binary_logloss: 0.676806\n",
      "[50]\tvalid_0's l1: 0.489185\tvalid_0's binary_logloss: 0.676426\n",
      "[51]\tvalid_0's l1: 0.489023\tvalid_0's binary_logloss: 0.676251\n",
      "[52]\tvalid_0's l1: 0.488809\tvalid_0's binary_logloss: 0.67603\n",
      "[53]\tvalid_0's l1: 0.48854\tvalid_0's binary_logloss: 0.675591\n",
      "[54]\tvalid_0's l1: 0.488333\tvalid_0's binary_logloss: 0.675407\n",
      "[55]\tvalid_0's l1: 0.488277\tvalid_0's binary_logloss: 0.675373\n",
      "[56]\tvalid_0's l1: 0.488113\tvalid_0's binary_logloss: 0.675294\n",
      "[57]\tvalid_0's l1: 0.487899\tvalid_0's binary_logloss: 0.67515\n",
      "[58]\tvalid_0's l1: 0.487749\tvalid_0's binary_logloss: 0.675151\n",
      "[59]\tvalid_0's l1: 0.487696\tvalid_0's binary_logloss: 0.675141\n",
      "[60]\tvalid_0's l1: 0.487531\tvalid_0's binary_logloss: 0.675131\n",
      "[61]\tvalid_0's l1: 0.487334\tvalid_0's binary_logloss: 0.675094\n",
      "[62]\tvalid_0's l1: 0.487244\tvalid_0's binary_logloss: 0.674955\n",
      "[63]\tvalid_0's l1: 0.487155\tvalid_0's binary_logloss: 0.674836\n",
      "[64]\tvalid_0's l1: 0.487122\tvalid_0's binary_logloss: 0.67488\n",
      "[65]\tvalid_0's l1: 0.486985\tvalid_0's binary_logloss: 0.674948\n",
      "[66]\tvalid_0's l1: 0.486898\tvalid_0's binary_logloss: 0.674846\n",
      "[67]\tvalid_0's l1: 0.48685\tvalid_0's binary_logloss: 0.674861\n",
      "[68]\tvalid_0's l1: 0.486814\tvalid_0's binary_logloss: 0.675031\n",
      "Early stopping, best iteration is:\n",
      "[63]\tvalid_0's l1: 0.487155\tvalid_0's binary_logloss: 0.674836\n",
      "[1]\tvalid_0's l1: 0.501037\tvalid_0's binary_logloss: 0.695769\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500797\tvalid_0's binary_logloss: 0.69527\n",
      "[3]\tvalid_0's l1: 0.500554\tvalid_0's binary_logloss: 0.694783\n",
      "[4]\tvalid_0's l1: 0.50048\tvalid_0's binary_logloss: 0.694633\n",
      "[5]\tvalid_0's l1: 0.500387\tvalid_0's binary_logloss: 0.694468\n",
      "[6]\tvalid_0's l1: 0.500453\tvalid_0's binary_logloss: 0.694621\n",
      "[7]\tvalid_0's l1: 0.500514\tvalid_0's binary_logloss: 0.694782\n",
      "[8]\tvalid_0's l1: 0.500457\tvalid_0's binary_logloss: 0.694724\n",
      "[9]\tvalid_0's l1: 0.500495\tvalid_0's binary_logloss: 0.694795\n",
      "[10]\tvalid_0's l1: 0.500397\tvalid_0's binary_logloss: 0.69462\n",
      "Early stopping, best iteration is:\n",
      "[5]\tvalid_0's l1: 0.500387\tvalid_0's binary_logloss: 0.694468\n",
      "[1]\tvalid_0's l1: 0.50108\tvalid_0's binary_logloss: 0.695823\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500872\tvalid_0's binary_logloss: 0.695376\n",
      "[3]\tvalid_0's l1: 0.50058\tvalid_0's binary_logloss: 0.694758\n",
      "[4]\tvalid_0's l1: 0.500335\tvalid_0's binary_logloss: 0.694294\n",
      "[5]\tvalid_0's l1: 0.500093\tvalid_0's binary_logloss: 0.69384\n",
      "[6]\tvalid_0's l1: 0.499801\tvalid_0's binary_logloss: 0.693316\n",
      "[7]\tvalid_0's l1: 0.499607\tvalid_0's binary_logloss: 0.693034\n",
      "[8]\tvalid_0's l1: 0.499328\tvalid_0's binary_logloss: 0.692587\n",
      "[9]\tvalid_0's l1: 0.49916\tvalid_0's binary_logloss: 0.692406\n",
      "[10]\tvalid_0's l1: 0.498886\tvalid_0's binary_logloss: 0.691969\n",
      "[11]\tvalid_0's l1: 0.498643\tvalid_0's binary_logloss: 0.691638\n",
      "[12]\tvalid_0's l1: 0.498311\tvalid_0's binary_logloss: 0.691128\n",
      "[13]\tvalid_0's l1: 0.497963\tvalid_0's binary_logloss: 0.690614\n",
      "[14]\tvalid_0's l1: 0.497912\tvalid_0's binary_logloss: 0.690641\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[15]\tvalid_0's l1: 0.497772\tvalid_0's binary_logloss: 0.69048\n",
      "[16]\tvalid_0's l1: 0.497748\tvalid_0's binary_logloss: 0.690591\n",
      "[17]\tvalid_0's l1: 0.497611\tvalid_0's binary_logloss: 0.690466\n",
      "[18]\tvalid_0's l1: 0.497475\tvalid_0's binary_logloss: 0.690367\n",
      "[19]\tvalid_0's l1: 0.497453\tvalid_0's binary_logloss: 0.690525\n",
      "[20]\tvalid_0's l1: 0.497402\tvalid_0's binary_logloss: 0.690599\n",
      "[21]\tvalid_0's l1: 0.497268\tvalid_0's binary_logloss: 0.690542\n",
      "[22]\tvalid_0's l1: 0.497142\tvalid_0's binary_logloss: 0.690513\n",
      "[23]\tvalid_0's l1: 0.49716\tvalid_0's binary_logloss: 0.690653\n",
      "Early stopping, best iteration is:\n",
      "[18]\tvalid_0's l1: 0.497475\tvalid_0's binary_logloss: 0.690367\n",
      "[1]\tvalid_0's l1: 0.501182\tvalid_0's binary_logloss: 0.696082\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501073\tvalid_0's binary_logloss: 0.695879\n",
      "[3]\tvalid_0's l1: 0.500988\tvalid_0's binary_logloss: 0.695703\n",
      "[4]\tvalid_0's l1: 0.500884\tvalid_0's binary_logloss: 0.695538\n",
      "[5]\tvalid_0's l1: 0.500784\tvalid_0's binary_logloss: 0.695323\n",
      "[6]\tvalid_0's l1: 0.500685\tvalid_0's binary_logloss: 0.695136\n",
      "[7]\tvalid_0's l1: 0.500591\tvalid_0's binary_logloss: 0.694986\n",
      "[8]\tvalid_0's l1: 0.500489\tvalid_0's binary_logloss: 0.694829\n",
      "[9]\tvalid_0's l1: 0.50041\tvalid_0's binary_logloss: 0.694733\n",
      "[10]\tvalid_0's l1: 0.500074\tvalid_0's binary_logloss: 0.694049\n",
      "[11]\tvalid_0's l1: 0.499963\tvalid_0's binary_logloss: 0.693916\n",
      "[12]\tvalid_0's l1: 0.499619\tvalid_0's binary_logloss: 0.693224\n",
      "[13]\tvalid_0's l1: 0.499487\tvalid_0's binary_logloss: 0.693074\n",
      "[14]\tvalid_0's l1: 0.499395\tvalid_0's binary_logloss: 0.69299\n",
      "[15]\tvalid_0's l1: 0.499178\tvalid_0's binary_logloss: 0.692686\n",
      "[16]\tvalid_0's l1: 0.498841\tvalid_0's binary_logloss: 0.692018\n",
      "[17]\tvalid_0's l1: 0.498758\tvalid_0's binary_logloss: 0.69198\n",
      "[18]\tvalid_0's l1: 0.498686\tvalid_0's binary_logloss: 0.692\n",
      "[19]\tvalid_0's l1: 0.498562\tvalid_0's binary_logloss: 0.691822\n",
      "[20]\tvalid_0's l1: 0.498373\tvalid_0's binary_logloss: 0.691624\n",
      "[21]\tvalid_0's l1: 0.498329\tvalid_0's binary_logloss: 0.691738\n",
      "[22]\tvalid_0's l1: 0.498207\tvalid_0's binary_logloss: 0.691594\n",
      "[23]\tvalid_0's l1: 0.498012\tvalid_0's binary_logloss: 0.691432\n",
      "[24]\tvalid_0's l1: 0.497893\tvalid_0's binary_logloss: 0.691317\n",
      "[25]\tvalid_0's l1: 0.497706\tvalid_0's binary_logloss: 0.691179\n",
      "[26]\tvalid_0's l1: 0.497515\tvalid_0's binary_logloss: 0.691066\n",
      "[27]\tvalid_0's l1: 0.497388\tvalid_0's binary_logloss: 0.690936\n",
      "[28]\tvalid_0's l1: 0.497212\tvalid_0's binary_logloss: 0.690849\n",
      "[29]\tvalid_0's l1: 0.497094\tvalid_0's binary_logloss: 0.690757\n",
      "[30]\tvalid_0's l1: 0.496965\tvalid_0's binary_logloss: 0.69079\n",
      "[31]\tvalid_0's l1: 0.496881\tvalid_0's binary_logloss: 0.690896\n",
      "[32]\tvalid_0's l1: 0.496776\tvalid_0's binary_logloss: 0.690881\n",
      "[33]\tvalid_0's l1: 0.496677\tvalid_0's binary_logloss: 0.690995\n",
      "[34]\tvalid_0's l1: 0.496566\tvalid_0's binary_logloss: 0.690989\n",
      "Early stopping, best iteration is:\n",
      "[29]\tvalid_0's l1: 0.497094\tvalid_0's binary_logloss: 0.690757\n",
      "[1]\tvalid_0's l1: 0.501023\tvalid_0's binary_logloss: 0.695841\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500733\tvalid_0's binary_logloss: 0.6953\n",
      "[3]\tvalid_0's l1: 0.500415\tvalid_0's binary_logloss: 0.694709\n",
      "[4]\tvalid_0's l1: 0.500148\tvalid_0's binary_logloss: 0.694267\n",
      "[5]\tvalid_0's l1: 0.499836\tvalid_0's binary_logloss: 0.69373\n",
      "[6]\tvalid_0's l1: 0.499575\tvalid_0's binary_logloss: 0.693341\n",
      "[7]\tvalid_0's l1: 0.499282\tvalid_0's binary_logloss: 0.692879\n",
      "[8]\tvalid_0's l1: 0.499094\tvalid_0's binary_logloss: 0.69265\n",
      "[9]\tvalid_0's l1: 0.498849\tvalid_0's binary_logloss: 0.69232\n",
      "[10]\tvalid_0's l1: 0.498665\tvalid_0's binary_logloss: 0.692129\n",
      "[11]\tvalid_0's l1: 0.498382\tvalid_0's binary_logloss: 0.691748\n",
      "[12]\tvalid_0's l1: 0.498012\tvalid_0's binary_logloss: 0.691198\n",
      "[13]\tvalid_0's l1: 0.497732\tvalid_0's binary_logloss: 0.690849\n",
      "[14]\tvalid_0's l1: 0.497554\tvalid_0's binary_logloss: 0.690583\n",
      "[15]\tvalid_0's l1: 0.497379\tvalid_0's binary_logloss: 0.69034\n",
      "[16]\tvalid_0's l1: 0.497218\tvalid_0's binary_logloss: 0.690146\n",
      "[17]\tvalid_0's l1: 0.497086\tvalid_0's binary_logloss: 0.690009\n",
      "[18]\tvalid_0's l1: 0.496941\tvalid_0's binary_logloss: 0.689882\n",
      "[19]\tvalid_0's l1: 0.496774\tvalid_0's binary_logloss: 0.689727\n",
      "[20]\tvalid_0's l1: 0.496632\tvalid_0's binary_logloss: 0.689641\n",
      "[21]\tvalid_0's l1: 0.496531\tvalid_0's binary_logloss: 0.689633\n",
      "[22]\tvalid_0's l1: 0.49643\tvalid_0's binary_logloss: 0.689566\n",
      "[23]\tvalid_0's l1: 0.496323\tvalid_0's binary_logloss: 0.68949\n",
      "[24]\tvalid_0's l1: 0.496004\tvalid_0's binary_logloss: 0.689148\n",
      "[25]\tvalid_0's l1: 0.495848\tvalid_0's binary_logloss: 0.689036\n",
      "[26]\tvalid_0's l1: 0.49575\tvalid_0's binary_logloss: 0.688981\n",
      "[27]\tvalid_0's l1: 0.495654\tvalid_0's binary_logloss: 0.688962\n",
      "[28]\tvalid_0's l1: 0.495601\tvalid_0's binary_logloss: 0.689001\n",
      "[29]\tvalid_0's l1: 0.4955\tvalid_0's binary_logloss: 0.688945\n",
      "[30]\tvalid_0's l1: 0.495301\tvalid_0's binary_logloss: 0.688823\n",
      "[31]\tvalid_0's l1: 0.49522\tvalid_0's binary_logloss: 0.688865\n",
      "[32]\tvalid_0's l1: 0.49511\tvalid_0's binary_logloss: 0.688851\n",
      "[33]\tvalid_0's l1: 0.494931\tvalid_0's binary_logloss: 0.688814\n",
      "[34]\tvalid_0's l1: 0.494864\tvalid_0's binary_logloss: 0.688899\n",
      "[35]\tvalid_0's l1: 0.494688\tvalid_0's binary_logloss: 0.688887\n",
      "[36]\tvalid_0's l1: 0.494644\tvalid_0's binary_logloss: 0.689028\n",
      "[37]\tvalid_0's l1: 0.494539\tvalid_0's binary_logloss: 0.689028\n",
      "[38]\tvalid_0's l1: 0.494408\tvalid_0's binary_logloss: 0.688962\n",
      "Early stopping, best iteration is:\n",
      "[33]\tvalid_0's l1: 0.494931\tvalid_0's binary_logloss: 0.688814\n",
      "[1]\tvalid_0's l1: 0.501059\tvalid_0's binary_logloss: 0.695877\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500792\tvalid_0's binary_logloss: 0.69535\n",
      "[3]\tvalid_0's l1: 0.500528\tvalid_0's binary_logloss: 0.694837\n",
      "[4]\tvalid_0's l1: 0.500165\tvalid_0's binary_logloss: 0.694078\n",
      "[5]\tvalid_0's l1: 0.499825\tvalid_0's binary_logloss: 0.693403\n",
      "[6]\tvalid_0's l1: 0.499567\tvalid_0's binary_logloss: 0.692919\n",
      "[7]\tvalid_0's l1: 0.499207\tvalid_0's binary_logloss: 0.692231\n",
      "[8]\tvalid_0's l1: 0.499002\tvalid_0's binary_logloss: 0.691876\n",
      "[9]\tvalid_0's l1: 0.498683\tvalid_0's binary_logloss: 0.691296\n",
      "[10]\tvalid_0's l1: 0.498595\tvalid_0's binary_logloss: 0.691118\n",
      "[11]\tvalid_0's l1: 0.498273\tvalid_0's binary_logloss: 0.690553\n",
      "[12]\tvalid_0's l1: 0.498075\tvalid_0's binary_logloss: 0.690227\n",
      "[13]\tvalid_0's l1: 0.497777\tvalid_0's binary_logloss: 0.689745\n",
      "[14]\tvalid_0's l1: 0.497693\tvalid_0's binary_logloss: 0.689588\n",
      "[15]\tvalid_0's l1: 0.497422\tvalid_0's binary_logloss: 0.689174\n",
      "[16]\tvalid_0's l1: 0.49723\tvalid_0's binary_logloss: 0.688876\n",
      "[17]\tvalid_0's l1: 0.496957\tvalid_0's binary_logloss: 0.688479\n",
      "[18]\tvalid_0's l1: 0.496877\tvalid_0's binary_logloss: 0.688341\n",
      "[19]\tvalid_0's l1: 0.496592\tvalid_0's binary_logloss: 0.68794\n",
      "[20]\tvalid_0's l1: 0.496407\tvalid_0's binary_logloss: 0.687668\n",
      "[21]\tvalid_0's l1: 0.496136\tvalid_0's binary_logloss: 0.68731\n",
      "[22]\tvalid_0's l1: 0.49606\tvalid_0's binary_logloss: 0.687188\n",
      "[23]\tvalid_0's l1: 0.495752\tvalid_0's binary_logloss: 0.686706\n",
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      "[25]\tvalid_0's l1: 0.495324\tvalid_0's binary_logloss: 0.686104\n",
      "[26]\tvalid_0's l1: 0.495106\tvalid_0's binary_logloss: 0.685772\n",
      "[27]\tvalid_0's l1: 0.494851\tvalid_0's binary_logloss: 0.685489\n",
      "[28]\tvalid_0's l1: 0.494775\tvalid_0's binary_logloss: 0.685409\n",
      "[29]\tvalid_0's l1: 0.494488\tvalid_0's binary_logloss: 0.685007\n",
      "[30]\tvalid_0's l1: 0.494389\tvalid_0's binary_logloss: 0.684902\n",
      "[31]\tvalid_0's l1: 0.494161\tvalid_0's binary_logloss: 0.684665\n",
      "[32]\tvalid_0's l1: 0.494105\tvalid_0's binary_logloss: 0.68474\n",
      "[33]\tvalid_0's l1: 0.493956\tvalid_0's binary_logloss: 0.684535\n",
      "[34]\tvalid_0's l1: 0.493776\tvalid_0's binary_logloss: 0.684263\n",
      "[35]\tvalid_0's l1: 0.493496\tvalid_0's binary_logloss: 0.683914\n",
      "[36]\tvalid_0's l1: 0.493485\tvalid_0's binary_logloss: 0.684086\n",
      "[37]\tvalid_0's l1: 0.493267\tvalid_0's binary_logloss: 0.683764\n",
      "[38]\tvalid_0's l1: 0.493088\tvalid_0's binary_logloss: 0.683502\n",
      "[39]\tvalid_0's l1: 0.492852\tvalid_0's binary_logloss: 0.683125\n",
      "[40]\tvalid_0's l1: 0.492634\tvalid_0's binary_logloss: 0.682925\n",
      "[41]\tvalid_0's l1: 0.492436\tvalid_0's binary_logloss: 0.682549\n",
      "[42]\tvalid_0's l1: 0.492194\tvalid_0's binary_logloss: 0.682111\n",
      "[43]\tvalid_0's l1: 0.492\tvalid_0's binary_logloss: 0.68178\n",
      "[44]\tvalid_0's l1: 0.491842\tvalid_0's binary_logloss: 0.681609\n",
      "[45]\tvalid_0's l1: 0.491661\tvalid_0's binary_logloss: 0.681271\n",
      "[46]\tvalid_0's l1: 0.491455\tvalid_0's binary_logloss: 0.680877\n",
      "[47]\tvalid_0's l1: 0.491174\tvalid_0's binary_logloss: 0.680414\n",
      "[48]\tvalid_0's l1: 0.490943\tvalid_0's binary_logloss: 0.68006\n",
      "[49]\tvalid_0's l1: 0.490707\tvalid_0's binary_logloss: 0.679862\n",
      "[50]\tvalid_0's l1: 0.490479\tvalid_0's binary_logloss: 0.679517\n",
      "[51]\tvalid_0's l1: 0.490313\tvalid_0's binary_logloss: 0.679306\n",
      "[52]\tvalid_0's l1: 0.490208\tvalid_0's binary_logloss: 0.679196\n",
      "[53]\tvalid_0's l1: 0.489906\tvalid_0's binary_logloss: 0.678806\n",
      "[54]\tvalid_0's l1: 0.489737\tvalid_0's binary_logloss: 0.678682\n",
      "[55]\tvalid_0's l1: 0.489695\tvalid_0's binary_logloss: 0.6787\n",
      "[56]\tvalid_0's l1: 0.489399\tvalid_0's binary_logloss: 0.678369\n",
      "[57]\tvalid_0's l1: 0.489234\tvalid_0's binary_logloss: 0.678299\n",
      "[58]\tvalid_0's l1: 0.489061\tvalid_0's binary_logloss: 0.678024\n",
      "[59]\tvalid_0's l1: 0.48889\tvalid_0's binary_logloss: 0.677972\n",
      "[60]\tvalid_0's l1: 0.488852\tvalid_0's binary_logloss: 0.678014\n",
      "[61]\tvalid_0's l1: 0.488566\tvalid_0's binary_logloss: 0.677764\n",
      "[62]\tvalid_0's l1: 0.4884\tvalid_0's binary_logloss: 0.677763\n",
      "[63]\tvalid_0's l1: 0.488169\tvalid_0's binary_logloss: 0.677607\n",
      "[64]\tvalid_0's l1: 0.487942\tvalid_0's binary_logloss: 0.677213\n",
      "[65]\tvalid_0's l1: 0.487737\tvalid_0's binary_logloss: 0.677199\n",
      "[66]\tvalid_0's l1: 0.487574\tvalid_0's binary_logloss: 0.677183\n",
      "[67]\tvalid_0's l1: 0.487388\tvalid_0's binary_logloss: 0.676848\n",
      "[68]\tvalid_0's l1: 0.487145\tvalid_0's binary_logloss: 0.67667\n",
      "[69]\tvalid_0's l1: 0.486931\tvalid_0's binary_logloss: 0.676461\n",
      "[70]\tvalid_0's l1: 0.486716\tvalid_0's binary_logloss: 0.676247\n",
      "[71]\tvalid_0's l1: 0.486564\tvalid_0's binary_logloss: 0.676086\n",
      "[72]\tvalid_0's l1: 0.486293\tvalid_0's binary_logloss: 0.675568\n",
      "[73]\tvalid_0's l1: 0.486089\tvalid_0's binary_logloss: 0.675237\n",
      "[74]\tvalid_0's l1: 0.486112\tvalid_0's binary_logloss: 0.675499\n",
      "[75]\tvalid_0's l1: 0.485844\tvalid_0's binary_logloss: 0.674997\n",
      "[76]\tvalid_0's l1: 0.485809\tvalid_0's binary_logloss: 0.675179\n",
      "[77]\tvalid_0's l1: 0.485813\tvalid_0's binary_logloss: 0.675434\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[78]\tvalid_0's l1: 0.485793\tvalid_0's binary_logloss: 0.675519\n",
      "[79]\tvalid_0's l1: 0.485586\tvalid_0's binary_logloss: 0.675146\n",
      "[80]\tvalid_0's l1: 0.485529\tvalid_0's binary_logloss: 0.675303\n",
      "Early stopping, best iteration is:\n",
      "[75]\tvalid_0's l1: 0.485844\tvalid_0's binary_logloss: 0.674997\n",
      "[1]\tvalid_0's l1: 0.501037\tvalid_0's binary_logloss: 0.695769\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500797\tvalid_0's binary_logloss: 0.69527\n",
      "[3]\tvalid_0's l1: 0.500554\tvalid_0's binary_logloss: 0.694783\n",
      "[4]\tvalid_0's l1: 0.50048\tvalid_0's binary_logloss: 0.694633\n",
      "[5]\tvalid_0's l1: 0.500387\tvalid_0's binary_logloss: 0.694468\n",
      "[6]\tvalid_0's l1: 0.500453\tvalid_0's binary_logloss: 0.694621\n",
      "[7]\tvalid_0's l1: 0.500514\tvalid_0's binary_logloss: 0.694782\n",
      "[8]\tvalid_0's l1: 0.500457\tvalid_0's binary_logloss: 0.694724\n",
      "[9]\tvalid_0's l1: 0.500507\tvalid_0's binary_logloss: 0.694816\n",
      "[10]\tvalid_0's l1: 0.500413\tvalid_0's binary_logloss: 0.694642\n",
      "Early stopping, best iteration is:\n",
      "[5]\tvalid_0's l1: 0.500387\tvalid_0's binary_logloss: 0.694468\n",
      "[1]\tvalid_0's l1: 0.50108\tvalid_0's binary_logloss: 0.695823\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500872\tvalid_0's binary_logloss: 0.695376\n",
      "[3]\tvalid_0's l1: 0.50058\tvalid_0's binary_logloss: 0.694758\n",
      "[4]\tvalid_0's l1: 0.500335\tvalid_0's binary_logloss: 0.694294\n",
      "[5]\tvalid_0's l1: 0.500093\tvalid_0's binary_logloss: 0.69384\n",
      "[6]\tvalid_0's l1: 0.499801\tvalid_0's binary_logloss: 0.693316\n",
      "[7]\tvalid_0's l1: 0.499607\tvalid_0's binary_logloss: 0.693034\n",
      "[8]\tvalid_0's l1: 0.499328\tvalid_0's binary_logloss: 0.692587\n",
      "[9]\tvalid_0's l1: 0.49916\tvalid_0's binary_logloss: 0.692406\n",
      "[10]\tvalid_0's l1: 0.498886\tvalid_0's binary_logloss: 0.691969\n",
      "[11]\tvalid_0's l1: 0.498666\tvalid_0's binary_logloss: 0.691683\n",
      "[12]\tvalid_0's l1: 0.49836\tvalid_0's binary_logloss: 0.691218\n",
      "[13]\tvalid_0's l1: 0.498014\tvalid_0's binary_logloss: 0.690696\n",
      "[14]\tvalid_0's l1: 0.497963\tvalid_0's binary_logloss: 0.690723\n",
      "[15]\tvalid_0's l1: 0.497823\tvalid_0's binary_logloss: 0.690562\n",
      "[16]\tvalid_0's l1: 0.497799\tvalid_0's binary_logloss: 0.690672\n",
      "[17]\tvalid_0's l1: 0.497662\tvalid_0's binary_logloss: 0.690546\n",
      "[18]\tvalid_0's l1: 0.49764\tvalid_0's binary_logloss: 0.690689\n",
      "[19]\tvalid_0's l1: 0.497504\tvalid_0's binary_logloss: 0.690605\n",
      "[20]\tvalid_0's l1: 0.497488\tvalid_0's binary_logloss: 0.690745\n",
      "[21]\tvalid_0's l1: 0.497355\tvalid_0's binary_logloss: 0.690686\n",
      "[22]\tvalid_0's l1: 0.497228\tvalid_0's binary_logloss: 0.690657\n",
      "Early stopping, best iteration is:\n",
      "[17]\tvalid_0's l1: 0.497662\tvalid_0's binary_logloss: 0.690546\n",
      "[1]\tvalid_0's l1: 0.501182\tvalid_0's binary_logloss: 0.696082\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501073\tvalid_0's binary_logloss: 0.695876\n",
      "[3]\tvalid_0's l1: 0.500996\tvalid_0's binary_logloss: 0.695717\n",
      "[4]\tvalid_0's l1: 0.500898\tvalid_0's binary_logloss: 0.695563\n",
      "[5]\tvalid_0's l1: 0.500798\tvalid_0's binary_logloss: 0.695349\n",
      "[6]\tvalid_0's l1: 0.500698\tvalid_0's binary_logloss: 0.695162\n",
      "[7]\tvalid_0's l1: 0.500605\tvalid_0's binary_logloss: 0.695011\n",
      "[8]\tvalid_0's l1: 0.500508\tvalid_0's binary_logloss: 0.694866\n",
      "[9]\tvalid_0's l1: 0.500424\tvalid_0's binary_logloss: 0.694759\n",
      "[10]\tvalid_0's l1: 0.500087\tvalid_0's binary_logloss: 0.694075\n",
      "[11]\tvalid_0's l1: 0.499977\tvalid_0's binary_logloss: 0.693942\n",
      "[12]\tvalid_0's l1: 0.499633\tvalid_0's binary_logloss: 0.693251\n",
      "[13]\tvalid_0's l1: 0.499501\tvalid_0's binary_logloss: 0.693101\n",
      "[14]\tvalid_0's l1: 0.499409\tvalid_0's binary_logloss: 0.693017\n",
      "[15]\tvalid_0's l1: 0.499192\tvalid_0's binary_logloss: 0.692713\n",
      "[16]\tvalid_0's l1: 0.498855\tvalid_0's binary_logloss: 0.692045\n",
      "[17]\tvalid_0's l1: 0.498766\tvalid_0's binary_logloss: 0.691996\n",
      "[18]\tvalid_0's l1: 0.498695\tvalid_0's binary_logloss: 0.692016\n",
      "[19]\tvalid_0's l1: 0.49857\tvalid_0's binary_logloss: 0.691837\n",
      "[20]\tvalid_0's l1: 0.498381\tvalid_0's binary_logloss: 0.691639\n",
      "[21]\tvalid_0's l1: 0.498265\tvalid_0's binary_logloss: 0.691607\n",
      "[22]\tvalid_0's l1: 0.498144\tvalid_0's binary_logloss: 0.691464\n",
      "[23]\tvalid_0's l1: 0.497901\tvalid_0's binary_logloss: 0.691201\n",
      "[24]\tvalid_0's l1: 0.497771\tvalid_0's binary_logloss: 0.691046\n",
      "[25]\tvalid_0's l1: 0.497702\tvalid_0's binary_logloss: 0.691148\n",
      "[26]\tvalid_0's l1: 0.497512\tvalid_0's binary_logloss: 0.691032\n",
      "[27]\tvalid_0's l1: 0.497395\tvalid_0's binary_logloss: 0.69095\n",
      "[28]\tvalid_0's l1: 0.497219\tvalid_0's binary_logloss: 0.690863\n",
      "[29]\tvalid_0's l1: 0.497035\tvalid_0's binary_logloss: 0.690812\n",
      "[30]\tvalid_0's l1: 0.496927\tvalid_0's binary_logloss: 0.690773\n",
      "[31]\tvalid_0's l1: 0.496906\tvalid_0's binary_logloss: 0.690997\n",
      "[32]\tvalid_0's l1: 0.496801\tvalid_0's binary_logloss: 0.690981\n",
      "[33]\tvalid_0's l1: 0.496752\tvalid_0's binary_logloss: 0.691188\n",
      "[34]\tvalid_0's l1: 0.496642\tvalid_0's binary_logloss: 0.691183\n",
      "[35]\tvalid_0's l1: 0.496498\tvalid_0's binary_logloss: 0.691208\n",
      "Early stopping, best iteration is:\n",
      "[30]\tvalid_0's l1: 0.496927\tvalid_0's binary_logloss: 0.690773\n",
      "[1]\tvalid_0's l1: 0.501\tvalid_0's binary_logloss: 0.695793\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500688\tvalid_0's binary_logloss: 0.695206\n",
      "[3]\tvalid_0's l1: 0.500347\tvalid_0's binary_logloss: 0.694573\n",
      "[4]\tvalid_0's l1: 0.500059\tvalid_0's binary_logloss: 0.694089\n",
      "[5]\tvalid_0's l1: 0.499725\tvalid_0's binary_logloss: 0.693513\n",
      "[6]\tvalid_0's l1: 0.49944\tvalid_0's binary_logloss: 0.693082\n",
      "[7]\tvalid_0's l1: 0.499152\tvalid_0's binary_logloss: 0.692649\n",
      "[8]\tvalid_0's l1: 0.498924\tvalid_0's binary_logloss: 0.69235\n",
      "[9]\tvalid_0's l1: 0.498724\tvalid_0's binary_logloss: 0.69209\n",
      "[10]\tvalid_0's l1: 0.498351\tvalid_0's binary_logloss: 0.691533\n",
      "[11]\tvalid_0's l1: 0.498196\tvalid_0's binary_logloss: 0.691399\n",
      "[12]\tvalid_0's l1: 0.497905\tvalid_0's binary_logloss: 0.691039\n",
      "[13]\tvalid_0's l1: 0.497565\tvalid_0's binary_logloss: 0.690567\n",
      "[14]\tvalid_0's l1: 0.497219\tvalid_0's binary_logloss: 0.690101\n",
      "[15]\tvalid_0's l1: 0.497032\tvalid_0's binary_logloss: 0.689824\n",
      "[16]\tvalid_0's l1: 0.496848\tvalid_0's binary_logloss: 0.689571\n",
      "[17]\tvalid_0's l1: 0.496676\tvalid_0's binary_logloss: 0.689362\n",
      "[18]\tvalid_0's l1: 0.496531\tvalid_0's binary_logloss: 0.689223\n",
      "[19]\tvalid_0's l1: 0.496394\tvalid_0's binary_logloss: 0.689099\n",
      "[20]\tvalid_0's l1: 0.496265\tvalid_0's binary_logloss: 0.689025\n",
      "[21]\tvalid_0's l1: 0.496078\tvalid_0's binary_logloss: 0.688857\n",
      "[22]\tvalid_0's l1: 0.495983\tvalid_0's binary_logloss: 0.688867\n",
      "[23]\tvalid_0's l1: 0.495806\tvalid_0's binary_logloss: 0.688751\n",
      "[24]\tvalid_0's l1: 0.49568\tvalid_0's binary_logloss: 0.688658\n",
      "[25]\tvalid_0's l1: 0.495549\tvalid_0's binary_logloss: 0.688514\n",
      "[26]\tvalid_0's l1: 0.495437\tvalid_0's binary_logloss: 0.688464\n",
      "[27]\tvalid_0's l1: 0.495361\tvalid_0's binary_logloss: 0.68854\n",
      "[28]\tvalid_0's l1: 0.495321\tvalid_0's binary_logloss: 0.688585\n",
      "[29]\tvalid_0's l1: 0.495207\tvalid_0's binary_logloss: 0.6885\n",
      "[30]\tvalid_0's l1: 0.495077\tvalid_0's binary_logloss: 0.688437\n",
      "[31]\tvalid_0's l1: 0.494997\tvalid_0's binary_logloss: 0.688482\n",
      "[32]\tvalid_0's l1: 0.494938\tvalid_0's binary_logloss: 0.688596\n",
      "[33]\tvalid_0's l1: 0.494759\tvalid_0's binary_logloss: 0.688554\n",
      "[34]\tvalid_0's l1: 0.494662\tvalid_0's binary_logloss: 0.688536\n",
      "[35]\tvalid_0's l1: 0.494537\tvalid_0's binary_logloss: 0.688529\n",
      "Early stopping, best iteration is:\n",
      "[30]\tvalid_0's l1: 0.495077\tvalid_0's binary_logloss: 0.688437\n",
      "[1]\tvalid_0's l1: 0.501059\tvalid_0's binary_logloss: 0.695877\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500792\tvalid_0's binary_logloss: 0.69535\n",
      "[3]\tvalid_0's l1: 0.500528\tvalid_0's binary_logloss: 0.694837\n",
      "[4]\tvalid_0's l1: 0.500132\tvalid_0's binary_logloss: 0.694018\n",
      "[5]\tvalid_0's l1: 0.499714\tvalid_0's binary_logloss: 0.693199\n",
      "[6]\tvalid_0's l1: 0.499456\tvalid_0's binary_logloss: 0.692716\n",
      "[7]\tvalid_0's l1: 0.499033\tvalid_0's binary_logloss: 0.691912\n",
      "[8]\tvalid_0's l1: 0.498829\tvalid_0's binary_logloss: 0.691559\n",
      "[9]\tvalid_0's l1: 0.498469\tvalid_0's binary_logloss: 0.690902\n",
      "[10]\tvalid_0's l1: 0.498382\tvalid_0's binary_logloss: 0.690723\n",
      "[11]\tvalid_0's l1: 0.498012\tvalid_0's binary_logloss: 0.690066\n",
      "[12]\tvalid_0's l1: 0.497839\tvalid_0's binary_logloss: 0.689741\n",
      "[13]\tvalid_0's l1: 0.497524\tvalid_0's binary_logloss: 0.689216\n",
      "[14]\tvalid_0's l1: 0.49733\tvalid_0's binary_logloss: 0.688906\n",
      "[15]\tvalid_0's l1: 0.496991\tvalid_0's binary_logloss: 0.68835\n",
      "[16]\tvalid_0's l1: 0.496811\tvalid_0's binary_logloss: 0.688019\n",
      "[17]\tvalid_0's l1: 0.496534\tvalid_0's binary_logloss: 0.68759\n",
      "[18]\tvalid_0's l1: 0.496316\tvalid_0's binary_logloss: 0.687135\n",
      "[19]\tvalid_0's l1: 0.495956\tvalid_0's binary_logloss: 0.686441\n",
      "[20]\tvalid_0's l1: 0.495617\tvalid_0's binary_logloss: 0.685924\n",
      "[21]\tvalid_0's l1: 0.495319\tvalid_0's binary_logloss: 0.6855\n",
      "[22]\tvalid_0's l1: 0.495132\tvalid_0's binary_logloss: 0.685178\n",
      "[23]\tvalid_0's l1: 0.494789\tvalid_0's binary_logloss: 0.684686\n",
      "[24]\tvalid_0's l1: 0.49456\tvalid_0's binary_logloss: 0.684245\n",
      "[25]\tvalid_0's l1: 0.494355\tvalid_0's binary_logloss: 0.683899\n",
      "[26]\tvalid_0's l1: 0.494248\tvalid_0's binary_logloss: 0.683756\n",
      "[27]\tvalid_0's l1: 0.493961\tvalid_0's binary_logloss: 0.683359\n",
      "[28]\tvalid_0's l1: 0.493782\tvalid_0's binary_logloss: 0.683073\n",
      "[29]\tvalid_0's l1: 0.493458\tvalid_0's binary_logloss: 0.682659\n",
      "[30]\tvalid_0's l1: 0.493296\tvalid_0's binary_logloss: 0.682451\n",
      "[31]\tvalid_0's l1: 0.493025\tvalid_0's binary_logloss: 0.6821\n",
      "[32]\tvalid_0's l1: 0.492859\tvalid_0's binary_logloss: 0.681884\n",
      "[33]\tvalid_0's l1: 0.492671\tvalid_0's binary_logloss: 0.681616\n",
      "[34]\tvalid_0's l1: 0.492521\tvalid_0's binary_logloss: 0.681326\n",
      "[35]\tvalid_0's l1: 0.492325\tvalid_0's binary_logloss: 0.681099\n",
      "[36]\tvalid_0's l1: 0.492141\tvalid_0's binary_logloss: 0.68084\n",
      "[37]\tvalid_0's l1: 0.491978\tvalid_0's binary_logloss: 0.68064\n",
      "[38]\tvalid_0's l1: 0.491689\tvalid_0's binary_logloss: 0.680165\n",
      "[39]\tvalid_0's l1: 0.49164\tvalid_0's binary_logloss: 0.680163\n",
      "[40]\tvalid_0's l1: 0.491473\tvalid_0's binary_logloss: 0.679946\n",
      "[41]\tvalid_0's l1: 0.491229\tvalid_0's binary_logloss: 0.679497\n",
      "[42]\tvalid_0's l1: 0.490988\tvalid_0's binary_logloss: 0.679073\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[43]\tvalid_0's l1: 0.490776\tvalid_0's binary_logloss: 0.678708\n",
      "[44]\tvalid_0's l1: 0.490418\tvalid_0's binary_logloss: 0.678144\n",
      "[45]\tvalid_0's l1: 0.490264\tvalid_0's binary_logloss: 0.67797\n",
      "[46]\tvalid_0's l1: 0.490051\tvalid_0's binary_logloss: 0.677627\n",
      "[47]\tvalid_0's l1: 0.489816\tvalid_0's binary_logloss: 0.677271\n",
      "[48]\tvalid_0's l1: 0.489601\tvalid_0's binary_logloss: 0.67695\n",
      "[49]\tvalid_0's l1: 0.489454\tvalid_0's binary_logloss: 0.676806\n",
      "[50]\tvalid_0's l1: 0.489185\tvalid_0's binary_logloss: 0.676426\n",
      "[51]\tvalid_0's l1: 0.489023\tvalid_0's binary_logloss: 0.676251\n",
      "[52]\tvalid_0's l1: 0.488809\tvalid_0's binary_logloss: 0.67603\n",
      "[53]\tvalid_0's l1: 0.48854\tvalid_0's binary_logloss: 0.675591\n",
      "[54]\tvalid_0's l1: 0.488333\tvalid_0's binary_logloss: 0.675407\n",
      "[55]\tvalid_0's l1: 0.488277\tvalid_0's binary_logloss: 0.675373\n",
      "[56]\tvalid_0's l1: 0.488113\tvalid_0's binary_logloss: 0.675294\n",
      "[57]\tvalid_0's l1: 0.487899\tvalid_0's binary_logloss: 0.67515\n",
      "[58]\tvalid_0's l1: 0.487749\tvalid_0's binary_logloss: 0.675151\n",
      "[59]\tvalid_0's l1: 0.487696\tvalid_0's binary_logloss: 0.675141\n",
      "[60]\tvalid_0's l1: 0.487531\tvalid_0's binary_logloss: 0.675131\n",
      "[61]\tvalid_0's l1: 0.487334\tvalid_0's binary_logloss: 0.675094\n",
      "[62]\tvalid_0's l1: 0.487244\tvalid_0's binary_logloss: 0.674955\n",
      "[63]\tvalid_0's l1: 0.487155\tvalid_0's binary_logloss: 0.674836\n",
      "[64]\tvalid_0's l1: 0.487122\tvalid_0's binary_logloss: 0.67488\n",
      "[65]\tvalid_0's l1: 0.486985\tvalid_0's binary_logloss: 0.674948\n",
      "[66]\tvalid_0's l1: 0.486898\tvalid_0's binary_logloss: 0.674846\n",
      "[67]\tvalid_0's l1: 0.48685\tvalid_0's binary_logloss: 0.674861\n",
      "[68]\tvalid_0's l1: 0.486814\tvalid_0's binary_logloss: 0.675031\n",
      "Early stopping, best iteration is:\n",
      "[63]\tvalid_0's l1: 0.487155\tvalid_0's binary_logloss: 0.674836\n",
      "[1]\tvalid_0's l1: 0.501037\tvalid_0's binary_logloss: 0.695769\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500797\tvalid_0's binary_logloss: 0.69527\n",
      "[3]\tvalid_0's l1: 0.500554\tvalid_0's binary_logloss: 0.694783\n",
      "[4]\tvalid_0's l1: 0.50048\tvalid_0's binary_logloss: 0.694633\n",
      "[5]\tvalid_0's l1: 0.500387\tvalid_0's binary_logloss: 0.694468\n",
      "[6]\tvalid_0's l1: 0.500453\tvalid_0's binary_logloss: 0.694621\n",
      "[7]\tvalid_0's l1: 0.500514\tvalid_0's binary_logloss: 0.694782\n",
      "[8]\tvalid_0's l1: 0.500457\tvalid_0's binary_logloss: 0.694724\n",
      "[9]\tvalid_0's l1: 0.500495\tvalid_0's binary_logloss: 0.694795\n",
      "[10]\tvalid_0's l1: 0.500397\tvalid_0's binary_logloss: 0.69462\n",
      "Early stopping, best iteration is:\n",
      "[5]\tvalid_0's l1: 0.500387\tvalid_0's binary_logloss: 0.694468\n",
      "[1]\tvalid_0's l1: 0.50108\tvalid_0's binary_logloss: 0.695823\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500872\tvalid_0's binary_logloss: 0.695376\n",
      "[3]\tvalid_0's l1: 0.50058\tvalid_0's binary_logloss: 0.694758\n",
      "[4]\tvalid_0's l1: 0.500335\tvalid_0's binary_logloss: 0.694294\n",
      "[5]\tvalid_0's l1: 0.500093\tvalid_0's binary_logloss: 0.69384\n",
      "[6]\tvalid_0's l1: 0.499801\tvalid_0's binary_logloss: 0.693316\n",
      "[7]\tvalid_0's l1: 0.499607\tvalid_0's binary_logloss: 0.693034\n",
      "[8]\tvalid_0's l1: 0.499328\tvalid_0's binary_logloss: 0.692587\n",
      "[9]\tvalid_0's l1: 0.49916\tvalid_0's binary_logloss: 0.692406\n",
      "[10]\tvalid_0's l1: 0.498886\tvalid_0's binary_logloss: 0.691969\n",
      "[11]\tvalid_0's l1: 0.498643\tvalid_0's binary_logloss: 0.691638\n",
      "[12]\tvalid_0's l1: 0.498311\tvalid_0's binary_logloss: 0.691128\n",
      "[13]\tvalid_0's l1: 0.497963\tvalid_0's binary_logloss: 0.690614\n",
      "[14]\tvalid_0's l1: 0.497912\tvalid_0's binary_logloss: 0.690641\n",
      "[15]\tvalid_0's l1: 0.497772\tvalid_0's binary_logloss: 0.69048\n",
      "[16]\tvalid_0's l1: 0.497748\tvalid_0's binary_logloss: 0.690591\n",
      "[17]\tvalid_0's l1: 0.497611\tvalid_0's binary_logloss: 0.690466\n",
      "[18]\tvalid_0's l1: 0.497475\tvalid_0's binary_logloss: 0.690367\n",
      "[19]\tvalid_0's l1: 0.497453\tvalid_0's binary_logloss: 0.690525\n",
      "[20]\tvalid_0's l1: 0.497402\tvalid_0's binary_logloss: 0.690599\n",
      "[21]\tvalid_0's l1: 0.497268\tvalid_0's binary_logloss: 0.690542\n",
      "[22]\tvalid_0's l1: 0.497142\tvalid_0's binary_logloss: 0.690513\n",
      "[23]\tvalid_0's l1: 0.49716\tvalid_0's binary_logloss: 0.690653\n",
      "Early stopping, best iteration is:\n",
      "[18]\tvalid_0's l1: 0.497475\tvalid_0's binary_logloss: 0.690367\n",
      "[1]\tvalid_0's l1: 0.501182\tvalid_0's binary_logloss: 0.696082\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501073\tvalid_0's binary_logloss: 0.695876\n",
      "[3]\tvalid_0's l1: 0.500996\tvalid_0's binary_logloss: 0.695717\n",
      "[4]\tvalid_0's l1: 0.500898\tvalid_0's binary_logloss: 0.695563\n",
      "[5]\tvalid_0's l1: 0.500798\tvalid_0's binary_logloss: 0.695349\n",
      "[6]\tvalid_0's l1: 0.500698\tvalid_0's binary_logloss: 0.695162\n",
      "[7]\tvalid_0's l1: 0.500605\tvalid_0's binary_logloss: 0.695011\n",
      "[8]\tvalid_0's l1: 0.500508\tvalid_0's binary_logloss: 0.694866\n",
      "[9]\tvalid_0's l1: 0.500424\tvalid_0's binary_logloss: 0.694759\n",
      "[10]\tvalid_0's l1: 0.500087\tvalid_0's binary_logloss: 0.694075\n",
      "[11]\tvalid_0's l1: 0.499977\tvalid_0's binary_logloss: 0.693942\n",
      "[12]\tvalid_0's l1: 0.499633\tvalid_0's binary_logloss: 0.693251\n",
      "[13]\tvalid_0's l1: 0.499501\tvalid_0's binary_logloss: 0.693101\n",
      "[14]\tvalid_0's l1: 0.499409\tvalid_0's binary_logloss: 0.693017\n",
      "[15]\tvalid_0's l1: 0.499192\tvalid_0's binary_logloss: 0.692713\n",
      "[16]\tvalid_0's l1: 0.498855\tvalid_0's binary_logloss: 0.692045\n",
      "[17]\tvalid_0's l1: 0.498766\tvalid_0's binary_logloss: 0.691996\n",
      "[18]\tvalid_0's l1: 0.498695\tvalid_0's binary_logloss: 0.692016\n",
      "[19]\tvalid_0's l1: 0.49857\tvalid_0's binary_logloss: 0.691837\n",
      "[20]\tvalid_0's l1: 0.498381\tvalid_0's binary_logloss: 0.691639\n",
      "[21]\tvalid_0's l1: 0.498265\tvalid_0's binary_logloss: 0.691607\n",
      "[22]\tvalid_0's l1: 0.498144\tvalid_0's binary_logloss: 0.691464\n",
      "[23]\tvalid_0's l1: 0.497901\tvalid_0's binary_logloss: 0.691201\n",
      "[24]\tvalid_0's l1: 0.497771\tvalid_0's binary_logloss: 0.691046\n",
      "[25]\tvalid_0's l1: 0.497702\tvalid_0's binary_logloss: 0.691148\n",
      "[26]\tvalid_0's l1: 0.497512\tvalid_0's binary_logloss: 0.691032\n",
      "[27]\tvalid_0's l1: 0.497395\tvalid_0's binary_logloss: 0.69095\n",
      "[28]\tvalid_0's l1: 0.497219\tvalid_0's binary_logloss: 0.690863\n",
      "[29]\tvalid_0's l1: 0.497035\tvalid_0's binary_logloss: 0.690812\n",
      "[30]\tvalid_0's l1: 0.496927\tvalid_0's binary_logloss: 0.690773\n",
      "[31]\tvalid_0's l1: 0.496906\tvalid_0's binary_logloss: 0.690997\n",
      "[32]\tvalid_0's l1: 0.496801\tvalid_0's binary_logloss: 0.690981\n",
      "[33]\tvalid_0's l1: 0.496752\tvalid_0's binary_logloss: 0.691188\n",
      "[34]\tvalid_0's l1: 0.496642\tvalid_0's binary_logloss: 0.691183\n",
      "[35]\tvalid_0's l1: 0.496498\tvalid_0's binary_logloss: 0.691208\n",
      "Early stopping, best iteration is:\n",
      "[30]\tvalid_0's l1: 0.496927\tvalid_0's binary_logloss: 0.690773\n",
      "[1]\tvalid_0's l1: 0.501\tvalid_0's binary_logloss: 0.695793\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500688\tvalid_0's binary_logloss: 0.695206\n",
      "[3]\tvalid_0's l1: 0.500347\tvalid_0's binary_logloss: 0.694573\n",
      "[4]\tvalid_0's l1: 0.500059\tvalid_0's binary_logloss: 0.694089\n",
      "[5]\tvalid_0's l1: 0.499725\tvalid_0's binary_logloss: 0.693513\n",
      "[6]\tvalid_0's l1: 0.49944\tvalid_0's binary_logloss: 0.693082\n",
      "[7]\tvalid_0's l1: 0.499152\tvalid_0's binary_logloss: 0.692649\n",
      "[8]\tvalid_0's l1: 0.498924\tvalid_0's binary_logloss: 0.69235\n",
      "[9]\tvalid_0's l1: 0.498724\tvalid_0's binary_logloss: 0.69209\n",
      "[10]\tvalid_0's l1: 0.498351\tvalid_0's binary_logloss: 0.691533\n",
      "[11]\tvalid_0's l1: 0.498196\tvalid_0's binary_logloss: 0.691399\n",
      "[12]\tvalid_0's l1: 0.497905\tvalid_0's binary_logloss: 0.691039\n",
      "[13]\tvalid_0's l1: 0.497565\tvalid_0's binary_logloss: 0.690567\n",
      "[14]\tvalid_0's l1: 0.497219\tvalid_0's binary_logloss: 0.690101\n",
      "[15]\tvalid_0's l1: 0.497032\tvalid_0's binary_logloss: 0.689824\n",
      "[16]\tvalid_0's l1: 0.496848\tvalid_0's binary_logloss: 0.689571\n",
      "[17]\tvalid_0's l1: 0.496676\tvalid_0's binary_logloss: 0.689362\n",
      "[18]\tvalid_0's l1: 0.496531\tvalid_0's binary_logloss: 0.689223\n",
      "[19]\tvalid_0's l1: 0.496394\tvalid_0's binary_logloss: 0.689099\n",
      "[20]\tvalid_0's l1: 0.496265\tvalid_0's binary_logloss: 0.689025\n",
      "[21]\tvalid_0's l1: 0.496078\tvalid_0's binary_logloss: 0.688857\n",
      "[22]\tvalid_0's l1: 0.495983\tvalid_0's binary_logloss: 0.688867\n",
      "[23]\tvalid_0's l1: 0.495806\tvalid_0's binary_logloss: 0.688751\n",
      "[24]\tvalid_0's l1: 0.49568\tvalid_0's binary_logloss: 0.688658\n",
      "[25]\tvalid_0's l1: 0.495549\tvalid_0's binary_logloss: 0.688514\n",
      "[26]\tvalid_0's l1: 0.495437\tvalid_0's binary_logloss: 0.688464\n",
      "[27]\tvalid_0's l1: 0.495361\tvalid_0's binary_logloss: 0.68854\n",
      "[28]\tvalid_0's l1: 0.495321\tvalid_0's binary_logloss: 0.688585\n",
      "[29]\tvalid_0's l1: 0.495207\tvalid_0's binary_logloss: 0.6885\n",
      "[30]\tvalid_0's l1: 0.495077\tvalid_0's binary_logloss: 0.688437\n",
      "[31]\tvalid_0's l1: 0.494997\tvalid_0's binary_logloss: 0.688482\n",
      "[32]\tvalid_0's l1: 0.494938\tvalid_0's binary_logloss: 0.688596\n",
      "[33]\tvalid_0's l1: 0.494759\tvalid_0's binary_logloss: 0.688554\n",
      "[34]\tvalid_0's l1: 0.494662\tvalid_0's binary_logloss: 0.688536\n",
      "[35]\tvalid_0's l1: 0.494537\tvalid_0's binary_logloss: 0.688529\n",
      "Early stopping, best iteration is:\n",
      "[30]\tvalid_0's l1: 0.495077\tvalid_0's binary_logloss: 0.688437\n",
      "[1]\tvalid_0's l1: 0.501059\tvalid_0's binary_logloss: 0.695877\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500792\tvalid_0's binary_logloss: 0.69535\n",
      "[3]\tvalid_0's l1: 0.500528\tvalid_0's binary_logloss: 0.694837\n",
      "[4]\tvalid_0's l1: 0.500132\tvalid_0's binary_logloss: 0.694018\n",
      "[5]\tvalid_0's l1: 0.499714\tvalid_0's binary_logloss: 0.693199\n",
      "[6]\tvalid_0's l1: 0.499456\tvalid_0's binary_logloss: 0.692716\n",
      "[7]\tvalid_0's l1: 0.499033\tvalid_0's binary_logloss: 0.691912\n",
      "[8]\tvalid_0's l1: 0.498829\tvalid_0's binary_logloss: 0.691559\n",
      "[9]\tvalid_0's l1: 0.498469\tvalid_0's binary_logloss: 0.690902\n",
      "[10]\tvalid_0's l1: 0.498382\tvalid_0's binary_logloss: 0.690723\n",
      "[11]\tvalid_0's l1: 0.498012\tvalid_0's binary_logloss: 0.690066\n",
      "[12]\tvalid_0's l1: 0.497839\tvalid_0's binary_logloss: 0.689741\n",
      "[13]\tvalid_0's l1: 0.497524\tvalid_0's binary_logloss: 0.689216\n",
      "[14]\tvalid_0's l1: 0.49733\tvalid_0's binary_logloss: 0.688906\n",
      "[15]\tvalid_0's l1: 0.496991\tvalid_0's binary_logloss: 0.68835\n",
      "[16]\tvalid_0's l1: 0.496811\tvalid_0's binary_logloss: 0.688019\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[17]\tvalid_0's l1: 0.496534\tvalid_0's binary_logloss: 0.68759\n",
      "[18]\tvalid_0's l1: 0.496316\tvalid_0's binary_logloss: 0.687135\n",
      "[19]\tvalid_0's l1: 0.495956\tvalid_0's binary_logloss: 0.686441\n",
      "[20]\tvalid_0's l1: 0.495617\tvalid_0's binary_logloss: 0.685924\n",
      "[21]\tvalid_0's l1: 0.495319\tvalid_0's binary_logloss: 0.6855\n",
      "[22]\tvalid_0's l1: 0.495132\tvalid_0's binary_logloss: 0.685178\n",
      "[23]\tvalid_0's l1: 0.494789\tvalid_0's binary_logloss: 0.684686\n",
      "[24]\tvalid_0's l1: 0.49456\tvalid_0's binary_logloss: 0.684245\n",
      "[25]\tvalid_0's l1: 0.494355\tvalid_0's binary_logloss: 0.683899\n",
      "[26]\tvalid_0's l1: 0.494248\tvalid_0's binary_logloss: 0.683756\n",
      "[27]\tvalid_0's l1: 0.493961\tvalid_0's binary_logloss: 0.683359\n",
      "[28]\tvalid_0's l1: 0.493782\tvalid_0's binary_logloss: 0.683073\n",
      "[29]\tvalid_0's l1: 0.493458\tvalid_0's binary_logloss: 0.682659\n",
      "[30]\tvalid_0's l1: 0.493296\tvalid_0's binary_logloss: 0.682451\n",
      "[31]\tvalid_0's l1: 0.493025\tvalid_0's binary_logloss: 0.6821\n",
      "[32]\tvalid_0's l1: 0.492859\tvalid_0's binary_logloss: 0.681884\n",
      "[33]\tvalid_0's l1: 0.492671\tvalid_0's binary_logloss: 0.681616\n",
      "[34]\tvalid_0's l1: 0.492521\tvalid_0's binary_logloss: 0.681326\n",
      "[35]\tvalid_0's l1: 0.492325\tvalid_0's binary_logloss: 0.681099\n",
      "[36]\tvalid_0's l1: 0.492141\tvalid_0's binary_logloss: 0.68084\n",
      "[37]\tvalid_0's l1: 0.491978\tvalid_0's binary_logloss: 0.68064\n",
      "[38]\tvalid_0's l1: 0.491689\tvalid_0's binary_logloss: 0.680165\n",
      "[39]\tvalid_0's l1: 0.49164\tvalid_0's binary_logloss: 0.680163\n",
      "[40]\tvalid_0's l1: 0.491473\tvalid_0's binary_logloss: 0.679946\n",
      "[41]\tvalid_0's l1: 0.491229\tvalid_0's binary_logloss: 0.679497\n",
      "[42]\tvalid_0's l1: 0.490988\tvalid_0's binary_logloss: 0.679073\n",
      "[43]\tvalid_0's l1: 0.490776\tvalid_0's binary_logloss: 0.678708\n",
      "[44]\tvalid_0's l1: 0.490418\tvalid_0's binary_logloss: 0.678144\n",
      "[45]\tvalid_0's l1: 0.490264\tvalid_0's binary_logloss: 0.67797\n",
      "[46]\tvalid_0's l1: 0.490051\tvalid_0's binary_logloss: 0.677627\n",
      "[47]\tvalid_0's l1: 0.489816\tvalid_0's binary_logloss: 0.677271\n",
      "[48]\tvalid_0's l1: 0.489601\tvalid_0's binary_logloss: 0.67695\n",
      "[49]\tvalid_0's l1: 0.489454\tvalid_0's binary_logloss: 0.676806\n",
      "[50]\tvalid_0's l1: 0.489185\tvalid_0's binary_logloss: 0.676426\n",
      "[51]\tvalid_0's l1: 0.489023\tvalid_0's binary_logloss: 0.676251\n",
      "[52]\tvalid_0's l1: 0.488809\tvalid_0's binary_logloss: 0.67603\n",
      "[53]\tvalid_0's l1: 0.48854\tvalid_0's binary_logloss: 0.675591\n",
      "[54]\tvalid_0's l1: 0.488333\tvalid_0's binary_logloss: 0.675407\n",
      "[55]\tvalid_0's l1: 0.488277\tvalid_0's binary_logloss: 0.675373\n",
      "[56]\tvalid_0's l1: 0.488113\tvalid_0's binary_logloss: 0.675294\n",
      "[57]\tvalid_0's l1: 0.487899\tvalid_0's binary_logloss: 0.67515\n",
      "[58]\tvalid_0's l1: 0.487749\tvalid_0's binary_logloss: 0.675151\n",
      "[59]\tvalid_0's l1: 0.487696\tvalid_0's binary_logloss: 0.675141\n",
      "[60]\tvalid_0's l1: 0.487531\tvalid_0's binary_logloss: 0.675131\n",
      "[61]\tvalid_0's l1: 0.487334\tvalid_0's binary_logloss: 0.675094\n",
      "[62]\tvalid_0's l1: 0.487244\tvalid_0's binary_logloss: 0.674955\n",
      "[63]\tvalid_0's l1: 0.487155\tvalid_0's binary_logloss: 0.674836\n",
      "[64]\tvalid_0's l1: 0.487122\tvalid_0's binary_logloss: 0.67488\n",
      "[65]\tvalid_0's l1: 0.486985\tvalid_0's binary_logloss: 0.674948\n",
      "[66]\tvalid_0's l1: 0.486898\tvalid_0's binary_logloss: 0.674846\n",
      "[67]\tvalid_0's l1: 0.48685\tvalid_0's binary_logloss: 0.674861\n",
      "[68]\tvalid_0's l1: 0.486814\tvalid_0's binary_logloss: 0.675031\n",
      "Early stopping, best iteration is:\n",
      "[63]\tvalid_0's l1: 0.487155\tvalid_0's binary_logloss: 0.674836\n",
      "[1]\tvalid_0's l1: 0.501037\tvalid_0's binary_logloss: 0.695769\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500797\tvalid_0's binary_logloss: 0.69527\n",
      "[3]\tvalid_0's l1: 0.500554\tvalid_0's binary_logloss: 0.694783\n",
      "[4]\tvalid_0's l1: 0.50048\tvalid_0's binary_logloss: 0.694633\n",
      "[5]\tvalid_0's l1: 0.500387\tvalid_0's binary_logloss: 0.694468\n",
      "[6]\tvalid_0's l1: 0.500453\tvalid_0's binary_logloss: 0.694621\n",
      "[7]\tvalid_0's l1: 0.500514\tvalid_0's binary_logloss: 0.694782\n",
      "[8]\tvalid_0's l1: 0.500457\tvalid_0's binary_logloss: 0.694724\n",
      "[9]\tvalid_0's l1: 0.500495\tvalid_0's binary_logloss: 0.694795\n",
      "[10]\tvalid_0's l1: 0.500397\tvalid_0's binary_logloss: 0.69462\n",
      "Early stopping, best iteration is:\n",
      "[5]\tvalid_0's l1: 0.500387\tvalid_0's binary_logloss: 0.694468\n",
      "[1]\tvalid_0's l1: 0.50108\tvalid_0's binary_logloss: 0.695823\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500872\tvalid_0's binary_logloss: 0.695376\n",
      "[3]\tvalid_0's l1: 0.50058\tvalid_0's binary_logloss: 0.694758\n",
      "[4]\tvalid_0's l1: 0.500335\tvalid_0's binary_logloss: 0.694294\n",
      "[5]\tvalid_0's l1: 0.500093\tvalid_0's binary_logloss: 0.69384\n",
      "[6]\tvalid_0's l1: 0.499801\tvalid_0's binary_logloss: 0.693316\n",
      "[7]\tvalid_0's l1: 0.499607\tvalid_0's binary_logloss: 0.693034\n",
      "[8]\tvalid_0's l1: 0.499328\tvalid_0's binary_logloss: 0.692587\n",
      "[9]\tvalid_0's l1: 0.49916\tvalid_0's binary_logloss: 0.692406\n",
      "[10]\tvalid_0's l1: 0.498886\tvalid_0's binary_logloss: 0.691969\n",
      "[11]\tvalid_0's l1: 0.498643\tvalid_0's binary_logloss: 0.691638\n",
      "[12]\tvalid_0's l1: 0.498311\tvalid_0's binary_logloss: 0.691128\n",
      "[13]\tvalid_0's l1: 0.497963\tvalid_0's binary_logloss: 0.690614\n",
      "[14]\tvalid_0's l1: 0.497912\tvalid_0's binary_logloss: 0.690641\n",
      "[15]\tvalid_0's l1: 0.497772\tvalid_0's binary_logloss: 0.69048\n",
      "[16]\tvalid_0's l1: 0.497748\tvalid_0's binary_logloss: 0.690591\n",
      "[17]\tvalid_0's l1: 0.497611\tvalid_0's binary_logloss: 0.690466\n",
      "[18]\tvalid_0's l1: 0.497475\tvalid_0's binary_logloss: 0.690367\n",
      "[19]\tvalid_0's l1: 0.497453\tvalid_0's binary_logloss: 0.690525\n",
      "[20]\tvalid_0's l1: 0.497402\tvalid_0's binary_logloss: 0.690599\n",
      "[21]\tvalid_0's l1: 0.497268\tvalid_0's binary_logloss: 0.690542\n",
      "[22]\tvalid_0's l1: 0.497142\tvalid_0's binary_logloss: 0.690513\n",
      "[23]\tvalid_0's l1: 0.49716\tvalid_0's binary_logloss: 0.690653\n",
      "Early stopping, best iteration is:\n",
      "[18]\tvalid_0's l1: 0.497475\tvalid_0's binary_logloss: 0.690367\n",
      "[1]\tvalid_0's l1: 0.500576\tvalid_0's binary_logloss: 0.694971\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500096\tvalid_0's binary_logloss: 0.694222\n",
      "[3]\tvalid_0's l1: 0.499463\tvalid_0's binary_logloss: 0.693457\n",
      "[4]\tvalid_0's l1: 0.498895\tvalid_0's binary_logloss: 0.693017\n",
      "[5]\tvalid_0's l1: 0.498289\tvalid_0's binary_logloss: 0.691866\n",
      "[6]\tvalid_0's l1: 0.498219\tvalid_0's binary_logloss: 0.692466\n",
      "[7]\tvalid_0's l1: 0.497659\tvalid_0's binary_logloss: 0.691796\n",
      "[8]\tvalid_0's l1: 0.497335\tvalid_0's binary_logloss: 0.691477\n",
      "[9]\tvalid_0's l1: 0.49625\tvalid_0's binary_logloss: 0.6894\n",
      "[10]\tvalid_0's l1: 0.495711\tvalid_0's binary_logloss: 0.688965\n",
      "[11]\tvalid_0's l1: 0.495213\tvalid_0's binary_logloss: 0.688901\n",
      "[12]\tvalid_0's l1: 0.494197\tvalid_0's binary_logloss: 0.687147\n",
      "[13]\tvalid_0's l1: 0.493689\tvalid_0's binary_logloss: 0.686774\n",
      "[14]\tvalid_0's l1: 0.493395\tvalid_0's binary_logloss: 0.687032\n",
      "[15]\tvalid_0's l1: 0.493841\tvalid_0's binary_logloss: 0.688205\n",
      "[16]\tvalid_0's l1: 0.49348\tvalid_0's binary_logloss: 0.688234\n",
      "[17]\tvalid_0's l1: 0.493117\tvalid_0's binary_logloss: 0.688097\n",
      "[18]\tvalid_0's l1: 0.493086\tvalid_0's binary_logloss: 0.689305\n",
      "Early stopping, best iteration is:\n",
      "[13]\tvalid_0's l1: 0.493689\tvalid_0's binary_logloss: 0.686774\n",
      "[1]\tvalid_0's l1: 0.500737\tvalid_0's binary_logloss: 0.695564\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.50032\tvalid_0's binary_logloss: 0.695191\n",
      "[3]\tvalid_0's l1: 0.49986\tvalid_0's binary_logloss: 0.694458\n",
      "[4]\tvalid_0's l1: 0.499483\tvalid_0's binary_logloss: 0.694457\n",
      "[5]\tvalid_0's l1: 0.498573\tvalid_0's binary_logloss: 0.692991\n",
      "[6]\tvalid_0's l1: 0.497851\tvalid_0's binary_logloss: 0.692124\n",
      "[7]\tvalid_0's l1: 0.497249\tvalid_0's binary_logloss: 0.691707\n",
      "[8]\tvalid_0's l1: 0.496735\tvalid_0's binary_logloss: 0.691526\n",
      "[9]\tvalid_0's l1: 0.496471\tvalid_0's binary_logloss: 0.692091\n",
      "[10]\tvalid_0's l1: 0.495847\tvalid_0's binary_logloss: 0.691747\n",
      "[11]\tvalid_0's l1: 0.495218\tvalid_0's binary_logloss: 0.691623\n",
      "[12]\tvalid_0's l1: 0.494414\tvalid_0's binary_logloss: 0.691076\n",
      "[13]\tvalid_0's l1: 0.493534\tvalid_0's binary_logloss: 0.689988\n",
      "[14]\tvalid_0's l1: 0.493393\tvalid_0's binary_logloss: 0.6898\n",
      "[15]\tvalid_0's l1: 0.493202\tvalid_0's binary_logloss: 0.69115\n",
      "[16]\tvalid_0's l1: 0.492078\tvalid_0's binary_logloss: 0.689618\n",
      "[17]\tvalid_0's l1: 0.491836\tvalid_0's binary_logloss: 0.689047\n",
      "[18]\tvalid_0's l1: 0.491683\tvalid_0's binary_logloss: 0.689397\n",
      "[19]\tvalid_0's l1: 0.491248\tvalid_0's binary_logloss: 0.69008\n",
      "[20]\tvalid_0's l1: 0.49089\tvalid_0's binary_logloss: 0.690189\n",
      "[21]\tvalid_0's l1: 0.490649\tvalid_0's binary_logloss: 0.690408\n",
      "[22]\tvalid_0's l1: 0.490411\tvalid_0's binary_logloss: 0.690084\n",
      "Early stopping, best iteration is:\n",
      "[17]\tvalid_0's l1: 0.491836\tvalid_0's binary_logloss: 0.689047\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1]\tvalid_0's l1: 0.500822\tvalid_0's binary_logloss: 0.695351\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500029\tvalid_0's binary_logloss: 0.693687\n",
      "[3]\tvalid_0's l1: 0.498879\tvalid_0's binary_logloss: 0.691416\n",
      "[4]\tvalid_0's l1: 0.498429\tvalid_0's binary_logloss: 0.690626\n",
      "[5]\tvalid_0's l1: 0.497793\tvalid_0's binary_logloss: 0.689541\n",
      "[6]\tvalid_0's l1: 0.497428\tvalid_0's binary_logloss: 0.688836\n",
      "[7]\tvalid_0's l1: 0.497053\tvalid_0's binary_logloss: 0.688041\n",
      "[8]\tvalid_0's l1: 0.496404\tvalid_0's binary_logloss: 0.687094\n",
      "[9]\tvalid_0's l1: 0.495943\tvalid_0's binary_logloss: 0.686418\n",
      "[10]\tvalid_0's l1: 0.495967\tvalid_0's binary_logloss: 0.686723\n",
      "[11]\tvalid_0's l1: 0.495192\tvalid_0's binary_logloss: 0.685508\n",
      "[12]\tvalid_0's l1: 0.494522\tvalid_0's binary_logloss: 0.684252\n",
      "[13]\tvalid_0's l1: 0.49417\tvalid_0's binary_logloss: 0.683861\n",
      "[14]\tvalid_0's l1: 0.494106\tvalid_0's binary_logloss: 0.68389\n",
      "[15]\tvalid_0's l1: 0.493531\tvalid_0's binary_logloss: 0.683348\n",
      "[16]\tvalid_0's l1: 0.492902\tvalid_0's binary_logloss: 0.682188\n",
      "[17]\tvalid_0's l1: 0.49236\tvalid_0's binary_logloss: 0.681809\n",
      "[18]\tvalid_0's l1: 0.49202\tvalid_0's binary_logloss: 0.681469\n",
      "[19]\tvalid_0's l1: 0.491816\tvalid_0's binary_logloss: 0.681272\n",
      "[20]\tvalid_0's l1: 0.491805\tvalid_0's binary_logloss: 0.681266\n",
      "[21]\tvalid_0's l1: 0.491494\tvalid_0's binary_logloss: 0.681037\n",
      "[22]\tvalid_0's l1: 0.491499\tvalid_0's binary_logloss: 0.681305\n",
      "[23]\tvalid_0's l1: 0.490849\tvalid_0's binary_logloss: 0.68063\n",
      "[24]\tvalid_0's l1: 0.490614\tvalid_0's binary_logloss: 0.68047\n",
      "[25]\tvalid_0's l1: 0.490417\tvalid_0's binary_logloss: 0.680062\n",
      "[26]\tvalid_0's l1: 0.49019\tvalid_0's binary_logloss: 0.680045\n",
      "[27]\tvalid_0's l1: 0.489578\tvalid_0's binary_logloss: 0.678968\n",
      "[28]\tvalid_0's l1: 0.489047\tvalid_0's binary_logloss: 0.678065\n",
      "[29]\tvalid_0's l1: 0.488772\tvalid_0's binary_logloss: 0.677937\n",
      "[30]\tvalid_0's l1: 0.488467\tvalid_0's binary_logloss: 0.677877\n",
      "[31]\tvalid_0's l1: 0.487583\tvalid_0's binary_logloss: 0.676103\n",
      "[32]\tvalid_0's l1: 0.486885\tvalid_0's binary_logloss: 0.674837\n",
      "[33]\tvalid_0's l1: 0.486682\tvalid_0's binary_logloss: 0.674775\n",
      "[34]\tvalid_0's l1: 0.486224\tvalid_0's binary_logloss: 0.674534\n",
      "[35]\tvalid_0's l1: 0.486069\tvalid_0's binary_logloss: 0.67462\n",
      "[36]\tvalid_0's l1: 0.486062\tvalid_0's binary_logloss: 0.674633\n",
      "[37]\tvalid_0's l1: 0.485946\tvalid_0's binary_logloss: 0.674186\n",
      "[38]\tvalid_0's l1: 0.485815\tvalid_0's binary_logloss: 0.674324\n",
      "[39]\tvalid_0's l1: 0.485263\tvalid_0's binary_logloss: 0.673945\n",
      "[40]\tvalid_0's l1: 0.485292\tvalid_0's binary_logloss: 0.674229\n",
      "[41]\tvalid_0's l1: 0.48557\tvalid_0's binary_logloss: 0.674776\n",
      "[42]\tvalid_0's l1: 0.48556\tvalid_0's binary_logloss: 0.674817\n",
      "[43]\tvalid_0's l1: 0.485295\tvalid_0's binary_logloss: 0.674401\n",
      "[44]\tvalid_0's l1: 0.485186\tvalid_0's binary_logloss: 0.673987\n",
      "Early stopping, best iteration is:\n",
      "[39]\tvalid_0's l1: 0.485263\tvalid_0's binary_logloss: 0.673945\n",
      "[1]\tvalid_0's l1: 0.500631\tvalid_0's binary_logloss: 0.694891\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500818\tvalid_0's binary_logloss: 0.695295\n",
      "[3]\tvalid_0's l1: 0.500916\tvalid_0's binary_logloss: 0.695609\n",
      "[4]\tvalid_0's l1: 0.500713\tvalid_0's binary_logloss: 0.695268\n",
      "[5]\tvalid_0's l1: 0.500844\tvalid_0's binary_logloss: 0.695611\n",
      "[6]\tvalid_0's l1: 0.500546\tvalid_0's binary_logloss: 0.695204\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l1: 0.500631\tvalid_0's binary_logloss: 0.694891\n",
      "[1]\tvalid_0's l1: 0.500616\tvalid_0's binary_logloss: 0.694936\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500514\tvalid_0's binary_logloss: 0.694931\n",
      "[3]\tvalid_0's l1: 0.499897\tvalid_0's binary_logloss: 0.694146\n",
      "[4]\tvalid_0's l1: 0.4998\tvalid_0's binary_logloss: 0.694404\n",
      "[5]\tvalid_0's l1: 0.500325\tvalid_0's binary_logloss: 0.695595\n",
      "[6]\tvalid_0's l1: 0.500239\tvalid_0's binary_logloss: 0.695985\n",
      "[7]\tvalid_0's l1: 0.500347\tvalid_0's binary_logloss: 0.696931\n",
      "[8]\tvalid_0's l1: 0.499872\tvalid_0's binary_logloss: 0.696682\n",
      "Early stopping, best iteration is:\n",
      "[3]\tvalid_0's l1: 0.499897\tvalid_0's binary_logloss: 0.694146\n",
      "[1]\tvalid_0's l1: 0.500576\tvalid_0's binary_logloss: 0.694971\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500096\tvalid_0's binary_logloss: 0.694222\n",
      "[3]\tvalid_0's l1: 0.499463\tvalid_0's binary_logloss: 0.693457\n",
      "[4]\tvalid_0's l1: 0.498895\tvalid_0's binary_logloss: 0.693017\n",
      "[5]\tvalid_0's l1: 0.498289\tvalid_0's binary_logloss: 0.691866\n",
      "[6]\tvalid_0's l1: 0.498219\tvalid_0's binary_logloss: 0.692466\n",
      "[7]\tvalid_0's l1: 0.497659\tvalid_0's binary_logloss: 0.691796\n",
      "[8]\tvalid_0's l1: 0.497335\tvalid_0's binary_logloss: 0.691477\n",
      "[9]\tvalid_0's l1: 0.49625\tvalid_0's binary_logloss: 0.6894\n",
      "[10]\tvalid_0's l1: 0.495711\tvalid_0's binary_logloss: 0.688965\n",
      "[11]\tvalid_0's l1: 0.495213\tvalid_0's binary_logloss: 0.688901\n",
      "[12]\tvalid_0's l1: 0.494197\tvalid_0's binary_logloss: 0.687147\n",
      "[13]\tvalid_0's l1: 0.493689\tvalid_0's binary_logloss: 0.686774\n",
      "[14]\tvalid_0's l1: 0.493395\tvalid_0's binary_logloss: 0.687032\n",
      "[15]\tvalid_0's l1: 0.493841\tvalid_0's binary_logloss: 0.688205\n",
      "[16]\tvalid_0's l1: 0.49348\tvalid_0's binary_logloss: 0.688234\n",
      "[17]\tvalid_0's l1: 0.493117\tvalid_0's binary_logloss: 0.688097\n",
      "[18]\tvalid_0's l1: 0.493086\tvalid_0's binary_logloss: 0.689305\n",
      "Early stopping, best iteration is:\n",
      "[13]\tvalid_0's l1: 0.493689\tvalid_0's binary_logloss: 0.686774\n",
      "[1]\tvalid_0's l1: 0.500737\tvalid_0's binary_logloss: 0.695564\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.50032\tvalid_0's binary_logloss: 0.695191\n",
      "[3]\tvalid_0's l1: 0.49986\tvalid_0's binary_logloss: 0.694458\n",
      "[4]\tvalid_0's l1: 0.499483\tvalid_0's binary_logloss: 0.694457\n",
      "[5]\tvalid_0's l1: 0.498573\tvalid_0's binary_logloss: 0.692991\n",
      "[6]\tvalid_0's l1: 0.497851\tvalid_0's binary_logloss: 0.692124\n",
      "[7]\tvalid_0's l1: 0.497249\tvalid_0's binary_logloss: 0.691707\n",
      "[8]\tvalid_0's l1: 0.496735\tvalid_0's binary_logloss: 0.691526\n",
      "[9]\tvalid_0's l1: 0.496471\tvalid_0's binary_logloss: 0.692091\n",
      "[10]\tvalid_0's l1: 0.495847\tvalid_0's binary_logloss: 0.691747\n",
      "[11]\tvalid_0's l1: 0.495218\tvalid_0's binary_logloss: 0.691623\n",
      "[12]\tvalid_0's l1: 0.494414\tvalid_0's binary_logloss: 0.691076\n",
      "[13]\tvalid_0's l1: 0.493534\tvalid_0's binary_logloss: 0.689988\n",
      "[14]\tvalid_0's l1: 0.493393\tvalid_0's binary_logloss: 0.6898\n",
      "[15]\tvalid_0's l1: 0.493202\tvalid_0's binary_logloss: 0.69115\n",
      "[16]\tvalid_0's l1: 0.492078\tvalid_0's binary_logloss: 0.689618\n",
      "[17]\tvalid_0's l1: 0.491836\tvalid_0's binary_logloss: 0.689047\n",
      "[18]\tvalid_0's l1: 0.491683\tvalid_0's binary_logloss: 0.689397\n",
      "[19]\tvalid_0's l1: 0.491248\tvalid_0's binary_logloss: 0.69008\n",
      "[20]\tvalid_0's l1: 0.49089\tvalid_0's binary_logloss: 0.690189\n",
      "[21]\tvalid_0's l1: 0.490649\tvalid_0's binary_logloss: 0.690408\n",
      "[22]\tvalid_0's l1: 0.490411\tvalid_0's binary_logloss: 0.690084\n",
      "Early stopping, best iteration is:\n",
      "[17]\tvalid_0's l1: 0.491836\tvalid_0's binary_logloss: 0.689047\n",
      "[1]\tvalid_0's l1: 0.500822\tvalid_0's binary_logloss: 0.695351\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500029\tvalid_0's binary_logloss: 0.693687\n",
      "[3]\tvalid_0's l1: 0.498879\tvalid_0's binary_logloss: 0.691416\n",
      "[4]\tvalid_0's l1: 0.498429\tvalid_0's binary_logloss: 0.690626\n",
      "[5]\tvalid_0's l1: 0.497793\tvalid_0's binary_logloss: 0.689541\n",
      "[6]\tvalid_0's l1: 0.497428\tvalid_0's binary_logloss: 0.688836\n",
      "[7]\tvalid_0's l1: 0.497053\tvalid_0's binary_logloss: 0.688041\n",
      "[8]\tvalid_0's l1: 0.496404\tvalid_0's binary_logloss: 0.687094\n",
      "[9]\tvalid_0's l1: 0.495943\tvalid_0's binary_logloss: 0.686418\n",
      "[10]\tvalid_0's l1: 0.495967\tvalid_0's binary_logloss: 0.686723\n",
      "[11]\tvalid_0's l1: 0.495192\tvalid_0's binary_logloss: 0.685508\n",
      "[12]\tvalid_0's l1: 0.494522\tvalid_0's binary_logloss: 0.684252\n",
      "[13]\tvalid_0's l1: 0.49417\tvalid_0's binary_logloss: 0.683861\n",
      "[14]\tvalid_0's l1: 0.494106\tvalid_0's binary_logloss: 0.68389\n",
      "[15]\tvalid_0's l1: 0.493531\tvalid_0's binary_logloss: 0.683348\n",
      "[16]\tvalid_0's l1: 0.492902\tvalid_0's binary_logloss: 0.682188\n",
      "[17]\tvalid_0's l1: 0.49236\tvalid_0's binary_logloss: 0.681809\n",
      "[18]\tvalid_0's l1: 0.49202\tvalid_0's binary_logloss: 0.681469\n",
      "[19]\tvalid_0's l1: 0.491816\tvalid_0's binary_logloss: 0.681272\n",
      "[20]\tvalid_0's l1: 0.491805\tvalid_0's binary_logloss: 0.681266\n",
      "[21]\tvalid_0's l1: 0.491494\tvalid_0's binary_logloss: 0.681037\n",
      "[22]\tvalid_0's l1: 0.491499\tvalid_0's binary_logloss: 0.681305\n",
      "[23]\tvalid_0's l1: 0.490849\tvalid_0's binary_logloss: 0.68063\n",
      "[24]\tvalid_0's l1: 0.490614\tvalid_0's binary_logloss: 0.68047\n",
      "[25]\tvalid_0's l1: 0.490417\tvalid_0's binary_logloss: 0.680062\n",
      "[26]\tvalid_0's l1: 0.49019\tvalid_0's binary_logloss: 0.680045\n",
      "[27]\tvalid_0's l1: 0.489578\tvalid_0's binary_logloss: 0.678968\n",
      "[28]\tvalid_0's l1: 0.489047\tvalid_0's binary_logloss: 0.678065\n",
      "[29]\tvalid_0's l1: 0.488772\tvalid_0's binary_logloss: 0.677937\n",
      "[30]\tvalid_0's l1: 0.488467\tvalid_0's binary_logloss: 0.677877\n",
      "[31]\tvalid_0's l1: 0.487583\tvalid_0's binary_logloss: 0.676103\n",
      "[32]\tvalid_0's l1: 0.486885\tvalid_0's binary_logloss: 0.674837\n",
      "[33]\tvalid_0's l1: 0.486682\tvalid_0's binary_logloss: 0.674775\n",
      "[34]\tvalid_0's l1: 0.486224\tvalid_0's binary_logloss: 0.674534\n",
      "[35]\tvalid_0's l1: 0.486069\tvalid_0's binary_logloss: 0.67462\n",
      "[36]\tvalid_0's l1: 0.486062\tvalid_0's binary_logloss: 0.674633\n",
      "[37]\tvalid_0's l1: 0.485946\tvalid_0's binary_logloss: 0.674186\n",
      "[38]\tvalid_0's l1: 0.485815\tvalid_0's binary_logloss: 0.674324\n",
      "[39]\tvalid_0's l1: 0.485263\tvalid_0's binary_logloss: 0.673945\n",
      "[40]\tvalid_0's l1: 0.485292\tvalid_0's binary_logloss: 0.674229\n",
      "[41]\tvalid_0's l1: 0.48557\tvalid_0's binary_logloss: 0.674776\n",
      "[42]\tvalid_0's l1: 0.48556\tvalid_0's binary_logloss: 0.674817\n",
      "[43]\tvalid_0's l1: 0.485295\tvalid_0's binary_logloss: 0.674401\n",
      "[44]\tvalid_0's l1: 0.485186\tvalid_0's binary_logloss: 0.673987\n",
      "Early stopping, best iteration is:\n",
      "[39]\tvalid_0's l1: 0.485263\tvalid_0's binary_logloss: 0.673945\n",
      "[1]\tvalid_0's l1: 0.500631\tvalid_0's binary_logloss: 0.694891\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500818\tvalid_0's binary_logloss: 0.695295\n",
      "[3]\tvalid_0's l1: 0.500916\tvalid_0's binary_logloss: 0.695609\n",
      "[4]\tvalid_0's l1: 0.500713\tvalid_0's binary_logloss: 0.695268\n",
      "[5]\tvalid_0's l1: 0.500844\tvalid_0's binary_logloss: 0.695611\n",
      "[6]\tvalid_0's l1: 0.500546\tvalid_0's binary_logloss: 0.695204\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l1: 0.500631\tvalid_0's binary_logloss: 0.694891\n",
      "[1]\tvalid_0's l1: 0.500616\tvalid_0's binary_logloss: 0.694936\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500514\tvalid_0's binary_logloss: 0.694931\n",
      "[3]\tvalid_0's l1: 0.499897\tvalid_0's binary_logloss: 0.694146\n",
      "[4]\tvalid_0's l1: 0.4998\tvalid_0's binary_logloss: 0.694404\n",
      "[5]\tvalid_0's l1: 0.500325\tvalid_0's binary_logloss: 0.695595\n",
      "[6]\tvalid_0's l1: 0.500239\tvalid_0's binary_logloss: 0.695985\n",
      "[7]\tvalid_0's l1: 0.500347\tvalid_0's binary_logloss: 0.696931\n",
      "[8]\tvalid_0's l1: 0.499872\tvalid_0's binary_logloss: 0.696682\n",
      "Early stopping, best iteration is:\n",
      "[3]\tvalid_0's l1: 0.499897\tvalid_0's binary_logloss: 0.694146\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1]\tvalid_0's l1: 0.500576\tvalid_0's binary_logloss: 0.694971\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500096\tvalid_0's binary_logloss: 0.694222\n",
      "[3]\tvalid_0's l1: 0.499463\tvalid_0's binary_logloss: 0.693457\n",
      "[4]\tvalid_0's l1: 0.498895\tvalid_0's binary_logloss: 0.693017\n",
      "[5]\tvalid_0's l1: 0.498289\tvalid_0's binary_logloss: 0.691866\n",
      "[6]\tvalid_0's l1: 0.498219\tvalid_0's binary_logloss: 0.692466\n",
      "[7]\tvalid_0's l1: 0.497659\tvalid_0's binary_logloss: 0.691796\n",
      "[8]\tvalid_0's l1: 0.497335\tvalid_0's binary_logloss: 0.691477\n",
      "[9]\tvalid_0's l1: 0.49625\tvalid_0's binary_logloss: 0.6894\n",
      "[10]\tvalid_0's l1: 0.495711\tvalid_0's binary_logloss: 0.688965\n",
      "[11]\tvalid_0's l1: 0.495213\tvalid_0's binary_logloss: 0.688901\n",
      "[12]\tvalid_0's l1: 0.494197\tvalid_0's binary_logloss: 0.687147\n",
      "[13]\tvalid_0's l1: 0.493689\tvalid_0's binary_logloss: 0.686774\n",
      "[14]\tvalid_0's l1: 0.493395\tvalid_0's binary_logloss: 0.687032\n",
      "[15]\tvalid_0's l1: 0.493841\tvalid_0's binary_logloss: 0.688205\n",
      "[16]\tvalid_0's l1: 0.49348\tvalid_0's binary_logloss: 0.688234\n",
      "[17]\tvalid_0's l1: 0.493117\tvalid_0's binary_logloss: 0.688097\n",
      "[18]\tvalid_0's l1: 0.493086\tvalid_0's binary_logloss: 0.689305\n",
      "Early stopping, best iteration is:\n",
      "[13]\tvalid_0's l1: 0.493689\tvalid_0's binary_logloss: 0.686774\n",
      "[1]\tvalid_0's l1: 0.500737\tvalid_0's binary_logloss: 0.695564\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.50032\tvalid_0's binary_logloss: 0.695191\n",
      "[3]\tvalid_0's l1: 0.49986\tvalid_0's binary_logloss: 0.694458\n",
      "[4]\tvalid_0's l1: 0.499483\tvalid_0's binary_logloss: 0.694457\n",
      "[5]\tvalid_0's l1: 0.498573\tvalid_0's binary_logloss: 0.692991\n",
      "[6]\tvalid_0's l1: 0.497851\tvalid_0's binary_logloss: 0.692124\n",
      "[7]\tvalid_0's l1: 0.497249\tvalid_0's binary_logloss: 0.691707\n",
      "[8]\tvalid_0's l1: 0.496735\tvalid_0's binary_logloss: 0.691526\n",
      "[9]\tvalid_0's l1: 0.496471\tvalid_0's binary_logloss: 0.692091\n",
      "[10]\tvalid_0's l1: 0.495847\tvalid_0's binary_logloss: 0.691747\n",
      "[11]\tvalid_0's l1: 0.495218\tvalid_0's binary_logloss: 0.691623\n",
      "[12]\tvalid_0's l1: 0.494414\tvalid_0's binary_logloss: 0.691076\n",
      "[13]\tvalid_0's l1: 0.493534\tvalid_0's binary_logloss: 0.689988\n",
      "[14]\tvalid_0's l1: 0.493393\tvalid_0's binary_logloss: 0.6898\n",
      "[15]\tvalid_0's l1: 0.493202\tvalid_0's binary_logloss: 0.69115\n",
      "[16]\tvalid_0's l1: 0.492078\tvalid_0's binary_logloss: 0.689618\n",
      "[17]\tvalid_0's l1: 0.491836\tvalid_0's binary_logloss: 0.689047\n",
      "[18]\tvalid_0's l1: 0.491683\tvalid_0's binary_logloss: 0.689397\n",
      "[19]\tvalid_0's l1: 0.491248\tvalid_0's binary_logloss: 0.69008\n",
      "[20]\tvalid_0's l1: 0.49089\tvalid_0's binary_logloss: 0.690189\n",
      "[21]\tvalid_0's l1: 0.490649\tvalid_0's binary_logloss: 0.690408\n",
      "[22]\tvalid_0's l1: 0.490411\tvalid_0's binary_logloss: 0.690084\n",
      "Early stopping, best iteration is:\n",
      "[17]\tvalid_0's l1: 0.491836\tvalid_0's binary_logloss: 0.689047\n",
      "[1]\tvalid_0's l1: 0.500822\tvalid_0's binary_logloss: 0.695351\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500029\tvalid_0's binary_logloss: 0.693687\n",
      "[3]\tvalid_0's l1: 0.498879\tvalid_0's binary_logloss: 0.691416\n",
      "[4]\tvalid_0's l1: 0.498429\tvalid_0's binary_logloss: 0.690626\n",
      "[5]\tvalid_0's l1: 0.497793\tvalid_0's binary_logloss: 0.689541\n",
      "[6]\tvalid_0's l1: 0.497428\tvalid_0's binary_logloss: 0.688836\n",
      "[7]\tvalid_0's l1: 0.497053\tvalid_0's binary_logloss: 0.688041\n",
      "[8]\tvalid_0's l1: 0.496404\tvalid_0's binary_logloss: 0.687094\n",
      "[9]\tvalid_0's l1: 0.495943\tvalid_0's binary_logloss: 0.686418\n",
      "[10]\tvalid_0's l1: 0.495967\tvalid_0's binary_logloss: 0.686723\n",
      "[11]\tvalid_0's l1: 0.495192\tvalid_0's binary_logloss: 0.685508\n",
      "[12]\tvalid_0's l1: 0.494522\tvalid_0's binary_logloss: 0.684252\n",
      "[13]\tvalid_0's l1: 0.49417\tvalid_0's binary_logloss: 0.683861\n",
      "[14]\tvalid_0's l1: 0.494106\tvalid_0's binary_logloss: 0.68389\n",
      "[15]\tvalid_0's l1: 0.493531\tvalid_0's binary_logloss: 0.683348\n",
      "[16]\tvalid_0's l1: 0.492902\tvalid_0's binary_logloss: 0.682188\n",
      "[17]\tvalid_0's l1: 0.49236\tvalid_0's binary_logloss: 0.681809\n",
      "[18]\tvalid_0's l1: 0.49202\tvalid_0's binary_logloss: 0.681469\n",
      "[19]\tvalid_0's l1: 0.491816\tvalid_0's binary_logloss: 0.681272\n",
      "[20]\tvalid_0's l1: 0.491805\tvalid_0's binary_logloss: 0.681266\n",
      "[21]\tvalid_0's l1: 0.491494\tvalid_0's binary_logloss: 0.681037\n",
      "[22]\tvalid_0's l1: 0.491499\tvalid_0's binary_logloss: 0.681305\n",
      "[23]\tvalid_0's l1: 0.490849\tvalid_0's binary_logloss: 0.68063\n",
      "[24]\tvalid_0's l1: 0.490614\tvalid_0's binary_logloss: 0.68047\n",
      "[25]\tvalid_0's l1: 0.490417\tvalid_0's binary_logloss: 0.680062\n",
      "[26]\tvalid_0's l1: 0.49019\tvalid_0's binary_logloss: 0.680045\n",
      "[27]\tvalid_0's l1: 0.489578\tvalid_0's binary_logloss: 0.678968\n",
      "[28]\tvalid_0's l1: 0.489047\tvalid_0's binary_logloss: 0.678065\n",
      "[29]\tvalid_0's l1: 0.488772\tvalid_0's binary_logloss: 0.677937\n",
      "[30]\tvalid_0's l1: 0.488467\tvalid_0's binary_logloss: 0.677877\n",
      "[31]\tvalid_0's l1: 0.487583\tvalid_0's binary_logloss: 0.676103\n",
      "[32]\tvalid_0's l1: 0.486885\tvalid_0's binary_logloss: 0.674837\n",
      "[33]\tvalid_0's l1: 0.486682\tvalid_0's binary_logloss: 0.674775\n",
      "[34]\tvalid_0's l1: 0.486224\tvalid_0's binary_logloss: 0.674534\n",
      "[35]\tvalid_0's l1: 0.486069\tvalid_0's binary_logloss: 0.67462\n",
      "[36]\tvalid_0's l1: 0.486062\tvalid_0's binary_logloss: 0.674633\n",
      "[37]\tvalid_0's l1: 0.485946\tvalid_0's binary_logloss: 0.674186\n",
      "[38]\tvalid_0's l1: 0.485815\tvalid_0's binary_logloss: 0.674324\n",
      "[39]\tvalid_0's l1: 0.485263\tvalid_0's binary_logloss: 0.673945\n",
      "[40]\tvalid_0's l1: 0.485292\tvalid_0's binary_logloss: 0.674229\n",
      "[41]\tvalid_0's l1: 0.48557\tvalid_0's binary_logloss: 0.674776\n",
      "[42]\tvalid_0's l1: 0.48556\tvalid_0's binary_logloss: 0.674817\n",
      "[43]\tvalid_0's l1: 0.485295\tvalid_0's binary_logloss: 0.674401\n",
      "[44]\tvalid_0's l1: 0.485186\tvalid_0's binary_logloss: 0.673987\n",
      "Early stopping, best iteration is:\n",
      "[39]\tvalid_0's l1: 0.485263\tvalid_0's binary_logloss: 0.673945\n",
      "[1]\tvalid_0's l1: 0.500631\tvalid_0's binary_logloss: 0.694891\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500818\tvalid_0's binary_logloss: 0.695295\n",
      "[3]\tvalid_0's l1: 0.500916\tvalid_0's binary_logloss: 0.695609\n",
      "[4]\tvalid_0's l1: 0.500713\tvalid_0's binary_logloss: 0.695268\n",
      "[5]\tvalid_0's l1: 0.500844\tvalid_0's binary_logloss: 0.695611\n",
      "[6]\tvalid_0's l1: 0.500546\tvalid_0's binary_logloss: 0.695204\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l1: 0.500631\tvalid_0's binary_logloss: 0.694891\n",
      "[1]\tvalid_0's l1: 0.500616\tvalid_0's binary_logloss: 0.694936\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500514\tvalid_0's binary_logloss: 0.694931\n",
      "[3]\tvalid_0's l1: 0.499897\tvalid_0's binary_logloss: 0.694146\n",
      "[4]\tvalid_0's l1: 0.4998\tvalid_0's binary_logloss: 0.694404\n",
      "[5]\tvalid_0's l1: 0.500325\tvalid_0's binary_logloss: 0.695595\n",
      "[6]\tvalid_0's l1: 0.500239\tvalid_0's binary_logloss: 0.695985\n",
      "[7]\tvalid_0's l1: 0.500347\tvalid_0's binary_logloss: 0.696931\n",
      "[8]\tvalid_0's l1: 0.499872\tvalid_0's binary_logloss: 0.696682\n",
      "Early stopping, best iteration is:\n",
      "[3]\tvalid_0's l1: 0.499897\tvalid_0's binary_logloss: 0.694146\n",
      "[1]\tvalid_0's l1: 0.500576\tvalid_0's binary_logloss: 0.694971\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500096\tvalid_0's binary_logloss: 0.694222\n",
      "[3]\tvalid_0's l1: 0.499463\tvalid_0's binary_logloss: 0.693457\n",
      "[4]\tvalid_0's l1: 0.498895\tvalid_0's binary_logloss: 0.693017\n",
      "[5]\tvalid_0's l1: 0.498289\tvalid_0's binary_logloss: 0.691866\n",
      "[6]\tvalid_0's l1: 0.498219\tvalid_0's binary_logloss: 0.692466\n",
      "[7]\tvalid_0's l1: 0.497659\tvalid_0's binary_logloss: 0.691796\n",
      "[8]\tvalid_0's l1: 0.497335\tvalid_0's binary_logloss: 0.691477\n",
      "[9]\tvalid_0's l1: 0.49625\tvalid_0's binary_logloss: 0.6894\n",
      "[10]\tvalid_0's l1: 0.495711\tvalid_0's binary_logloss: 0.688965\n",
      "[11]\tvalid_0's l1: 0.495213\tvalid_0's binary_logloss: 0.688901\n",
      "[12]\tvalid_0's l1: 0.494197\tvalid_0's binary_logloss: 0.687147\n",
      "[13]\tvalid_0's l1: 0.493689\tvalid_0's binary_logloss: 0.686774\n",
      "[14]\tvalid_0's l1: 0.493395\tvalid_0's binary_logloss: 0.687032\n",
      "[15]\tvalid_0's l1: 0.493841\tvalid_0's binary_logloss: 0.688205\n",
      "[16]\tvalid_0's l1: 0.49348\tvalid_0's binary_logloss: 0.688234\n",
      "[17]\tvalid_0's l1: 0.493117\tvalid_0's binary_logloss: 0.688097\n",
      "[18]\tvalid_0's l1: 0.493086\tvalid_0's binary_logloss: 0.689305\n",
      "Early stopping, best iteration is:\n",
      "[13]\tvalid_0's l1: 0.493689\tvalid_0's binary_logloss: 0.686774\n",
      "[1]\tvalid_0's l1: 0.500737\tvalid_0's binary_logloss: 0.695564\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.50032\tvalid_0's binary_logloss: 0.695191\n",
      "[3]\tvalid_0's l1: 0.49986\tvalid_0's binary_logloss: 0.694458\n",
      "[4]\tvalid_0's l1: 0.499483\tvalid_0's binary_logloss: 0.694457\n",
      "[5]\tvalid_0's l1: 0.498573\tvalid_0's binary_logloss: 0.692991\n",
      "[6]\tvalid_0's l1: 0.497851\tvalid_0's binary_logloss: 0.692124\n",
      "[7]\tvalid_0's l1: 0.497249\tvalid_0's binary_logloss: 0.691707\n",
      "[8]\tvalid_0's l1: 0.496735\tvalid_0's binary_logloss: 0.691526\n",
      "[9]\tvalid_0's l1: 0.496471\tvalid_0's binary_logloss: 0.692091\n",
      "[10]\tvalid_0's l1: 0.495847\tvalid_0's binary_logloss: 0.691747\n",
      "[11]\tvalid_0's l1: 0.495218\tvalid_0's binary_logloss: 0.691623\n",
      "[12]\tvalid_0's l1: 0.494414\tvalid_0's binary_logloss: 0.691076\n",
      "[13]\tvalid_0's l1: 0.493534\tvalid_0's binary_logloss: 0.689988\n",
      "[14]\tvalid_0's l1: 0.493393\tvalid_0's binary_logloss: 0.6898\n",
      "[15]\tvalid_0's l1: 0.493202\tvalid_0's binary_logloss: 0.69115\n",
      "[16]\tvalid_0's l1: 0.492078\tvalid_0's binary_logloss: 0.689618\n",
      "[17]\tvalid_0's l1: 0.491836\tvalid_0's binary_logloss: 0.689047\n",
      "[18]\tvalid_0's l1: 0.491683\tvalid_0's binary_logloss: 0.689397\n",
      "[19]\tvalid_0's l1: 0.491248\tvalid_0's binary_logloss: 0.69008\n",
      "[20]\tvalid_0's l1: 0.49089\tvalid_0's binary_logloss: 0.690189\n",
      "[21]\tvalid_0's l1: 0.490649\tvalid_0's binary_logloss: 0.690408\n",
      "[22]\tvalid_0's l1: 0.490411\tvalid_0's binary_logloss: 0.690084\n",
      "Early stopping, best iteration is:\n",
      "[17]\tvalid_0's l1: 0.491836\tvalid_0's binary_logloss: 0.689047\n",
      "[1]\tvalid_0's l1: 0.500822\tvalid_0's binary_logloss: 0.695351\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500029\tvalid_0's binary_logloss: 0.693687\n",
      "[3]\tvalid_0's l1: 0.498879\tvalid_0's binary_logloss: 0.691416\n",
      "[4]\tvalid_0's l1: 0.498429\tvalid_0's binary_logloss: 0.690626\n",
      "[5]\tvalid_0's l1: 0.497793\tvalid_0's binary_logloss: 0.689541\n",
      "[6]\tvalid_0's l1: 0.497428\tvalid_0's binary_logloss: 0.688836\n",
      "[7]\tvalid_0's l1: 0.497053\tvalid_0's binary_logloss: 0.688041\n",
      "[8]\tvalid_0's l1: 0.496404\tvalid_0's binary_logloss: 0.687094\n",
      "[9]\tvalid_0's l1: 0.495943\tvalid_0's binary_logloss: 0.686418\n",
      "[10]\tvalid_0's l1: 0.495967\tvalid_0's binary_logloss: 0.686723\n",
      "[11]\tvalid_0's l1: 0.495192\tvalid_0's binary_logloss: 0.685508\n",
      "[12]\tvalid_0's l1: 0.494522\tvalid_0's binary_logloss: 0.684252\n",
      "[13]\tvalid_0's l1: 0.49417\tvalid_0's binary_logloss: 0.683861\n",
      "[14]\tvalid_0's l1: 0.494106\tvalid_0's binary_logloss: 0.68389\n",
      "[15]\tvalid_0's l1: 0.493531\tvalid_0's binary_logloss: 0.683348\n",
      "[16]\tvalid_0's l1: 0.492902\tvalid_0's binary_logloss: 0.682188\n",
      "[17]\tvalid_0's l1: 0.49236\tvalid_0's binary_logloss: 0.681809\n",
      "[18]\tvalid_0's l1: 0.49202\tvalid_0's binary_logloss: 0.681469\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[19]\tvalid_0's l1: 0.491816\tvalid_0's binary_logloss: 0.681272\n",
      "[20]\tvalid_0's l1: 0.491805\tvalid_0's binary_logloss: 0.681266\n",
      "[21]\tvalid_0's l1: 0.491494\tvalid_0's binary_logloss: 0.681037\n",
      "[22]\tvalid_0's l1: 0.491499\tvalid_0's binary_logloss: 0.681305\n",
      "[23]\tvalid_0's l1: 0.490849\tvalid_0's binary_logloss: 0.68063\n",
      "[24]\tvalid_0's l1: 0.490614\tvalid_0's binary_logloss: 0.68047\n",
      "[25]\tvalid_0's l1: 0.490417\tvalid_0's binary_logloss: 0.680062\n",
      "[26]\tvalid_0's l1: 0.49019\tvalid_0's binary_logloss: 0.680045\n",
      "[27]\tvalid_0's l1: 0.489578\tvalid_0's binary_logloss: 0.678968\n",
      "[28]\tvalid_0's l1: 0.489047\tvalid_0's binary_logloss: 0.678065\n",
      "[29]\tvalid_0's l1: 0.488772\tvalid_0's binary_logloss: 0.677937\n",
      "[30]\tvalid_0's l1: 0.488467\tvalid_0's binary_logloss: 0.677877\n",
      "[31]\tvalid_0's l1: 0.487583\tvalid_0's binary_logloss: 0.676103\n",
      "[32]\tvalid_0's l1: 0.486885\tvalid_0's binary_logloss: 0.674837\n",
      "[33]\tvalid_0's l1: 0.486682\tvalid_0's binary_logloss: 0.674775\n",
      "[34]\tvalid_0's l1: 0.486224\tvalid_0's binary_logloss: 0.674534\n",
      "[35]\tvalid_0's l1: 0.486069\tvalid_0's binary_logloss: 0.67462\n",
      "[36]\tvalid_0's l1: 0.486062\tvalid_0's binary_logloss: 0.674633\n",
      "[37]\tvalid_0's l1: 0.485946\tvalid_0's binary_logloss: 0.674186\n",
      "[38]\tvalid_0's l1: 0.485815\tvalid_0's binary_logloss: 0.674324\n",
      "[39]\tvalid_0's l1: 0.485263\tvalid_0's binary_logloss: 0.673945\n",
      "[40]\tvalid_0's l1: 0.485292\tvalid_0's binary_logloss: 0.674229\n",
      "[41]\tvalid_0's l1: 0.48557\tvalid_0's binary_logloss: 0.674776\n",
      "[42]\tvalid_0's l1: 0.48556\tvalid_0's binary_logloss: 0.674817\n",
      "[43]\tvalid_0's l1: 0.485295\tvalid_0's binary_logloss: 0.674401\n",
      "[44]\tvalid_0's l1: 0.485186\tvalid_0's binary_logloss: 0.673987\n",
      "Early stopping, best iteration is:\n",
      "[39]\tvalid_0's l1: 0.485263\tvalid_0's binary_logloss: 0.673945\n",
      "[1]\tvalid_0's l1: 0.500631\tvalid_0's binary_logloss: 0.694891\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500818\tvalid_0's binary_logloss: 0.695295\n",
      "[3]\tvalid_0's l1: 0.500916\tvalid_0's binary_logloss: 0.695609\n",
      "[4]\tvalid_0's l1: 0.500713\tvalid_0's binary_logloss: 0.695268\n",
      "[5]\tvalid_0's l1: 0.500844\tvalid_0's binary_logloss: 0.695611\n",
      "[6]\tvalid_0's l1: 0.500546\tvalid_0's binary_logloss: 0.695204\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l1: 0.500631\tvalid_0's binary_logloss: 0.694891\n",
      "[1]\tvalid_0's l1: 0.500616\tvalid_0's binary_logloss: 0.694936\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500514\tvalid_0's binary_logloss: 0.694931\n",
      "[3]\tvalid_0's l1: 0.499897\tvalid_0's binary_logloss: 0.694146\n",
      "[4]\tvalid_0's l1: 0.4998\tvalid_0's binary_logloss: 0.694404\n",
      "[5]\tvalid_0's l1: 0.500325\tvalid_0's binary_logloss: 0.695595\n",
      "[6]\tvalid_0's l1: 0.500239\tvalid_0's binary_logloss: 0.695985\n",
      "[7]\tvalid_0's l1: 0.500347\tvalid_0's binary_logloss: 0.696931\n",
      "[8]\tvalid_0's l1: 0.499872\tvalid_0's binary_logloss: 0.696682\n",
      "Early stopping, best iteration is:\n",
      "[3]\tvalid_0's l1: 0.499897\tvalid_0's binary_logloss: 0.694146\n",
      "[1]\tvalid_0's l1: 0.500576\tvalid_0's binary_logloss: 0.694971\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500096\tvalid_0's binary_logloss: 0.694222\n",
      "[3]\tvalid_0's l1: 0.499463\tvalid_0's binary_logloss: 0.693457\n",
      "[4]\tvalid_0's l1: 0.498895\tvalid_0's binary_logloss: 0.693017\n",
      "[5]\tvalid_0's l1: 0.498289\tvalid_0's binary_logloss: 0.691866\n",
      "[6]\tvalid_0's l1: 0.498219\tvalid_0's binary_logloss: 0.692466\n",
      "[7]\tvalid_0's l1: 0.497659\tvalid_0's binary_logloss: 0.691796\n",
      "[8]\tvalid_0's l1: 0.497335\tvalid_0's binary_logloss: 0.691477\n",
      "[9]\tvalid_0's l1: 0.49625\tvalid_0's binary_logloss: 0.6894\n",
      "[10]\tvalid_0's l1: 0.495711\tvalid_0's binary_logloss: 0.688965\n",
      "[11]\tvalid_0's l1: 0.495213\tvalid_0's binary_logloss: 0.688901\n",
      "[12]\tvalid_0's l1: 0.494197\tvalid_0's binary_logloss: 0.687147\n",
      "[13]\tvalid_0's l1: 0.493689\tvalid_0's binary_logloss: 0.686774\n",
      "[14]\tvalid_0's l1: 0.493395\tvalid_0's binary_logloss: 0.687032\n",
      "[15]\tvalid_0's l1: 0.493841\tvalid_0's binary_logloss: 0.688205\n",
      "[16]\tvalid_0's l1: 0.49348\tvalid_0's binary_logloss: 0.688234\n",
      "[17]\tvalid_0's l1: 0.493117\tvalid_0's binary_logloss: 0.688097\n",
      "[18]\tvalid_0's l1: 0.493086\tvalid_0's binary_logloss: 0.689305\n",
      "Early stopping, best iteration is:\n",
      "[13]\tvalid_0's l1: 0.493689\tvalid_0's binary_logloss: 0.686774\n",
      "[1]\tvalid_0's l1: 0.500737\tvalid_0's binary_logloss: 0.695564\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.50032\tvalid_0's binary_logloss: 0.695191\n",
      "[3]\tvalid_0's l1: 0.49986\tvalid_0's binary_logloss: 0.694458\n",
      "[4]\tvalid_0's l1: 0.499483\tvalid_0's binary_logloss: 0.694457\n",
      "[5]\tvalid_0's l1: 0.498573\tvalid_0's binary_logloss: 0.692991\n",
      "[6]\tvalid_0's l1: 0.497851\tvalid_0's binary_logloss: 0.692124\n",
      "[7]\tvalid_0's l1: 0.497249\tvalid_0's binary_logloss: 0.691707\n",
      "[8]\tvalid_0's l1: 0.496735\tvalid_0's binary_logloss: 0.691526\n",
      "[9]\tvalid_0's l1: 0.496471\tvalid_0's binary_logloss: 0.692091\n",
      "[10]\tvalid_0's l1: 0.495847\tvalid_0's binary_logloss: 0.691747\n",
      "[11]\tvalid_0's l1: 0.495218\tvalid_0's binary_logloss: 0.691623\n",
      "[12]\tvalid_0's l1: 0.494414\tvalid_0's binary_logloss: 0.691076\n",
      "[13]\tvalid_0's l1: 0.493534\tvalid_0's binary_logloss: 0.689988\n",
      "[14]\tvalid_0's l1: 0.493393\tvalid_0's binary_logloss: 0.6898\n",
      "[15]\tvalid_0's l1: 0.493202\tvalid_0's binary_logloss: 0.69115\n",
      "[16]\tvalid_0's l1: 0.492078\tvalid_0's binary_logloss: 0.689618\n",
      "[17]\tvalid_0's l1: 0.491836\tvalid_0's binary_logloss: 0.689047\n",
      "[18]\tvalid_0's l1: 0.491683\tvalid_0's binary_logloss: 0.689397\n",
      "[19]\tvalid_0's l1: 0.491248\tvalid_0's binary_logloss: 0.69008\n",
      "[20]\tvalid_0's l1: 0.49089\tvalid_0's binary_logloss: 0.690189\n",
      "[21]\tvalid_0's l1: 0.490649\tvalid_0's binary_logloss: 0.690408\n",
      "[22]\tvalid_0's l1: 0.490411\tvalid_0's binary_logloss: 0.690084\n",
      "Early stopping, best iteration is:\n",
      "[17]\tvalid_0's l1: 0.491836\tvalid_0's binary_logloss: 0.689047\n",
      "[1]\tvalid_0's l1: 0.500822\tvalid_0's binary_logloss: 0.695351\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500029\tvalid_0's binary_logloss: 0.693687\n",
      "[3]\tvalid_0's l1: 0.498879\tvalid_0's binary_logloss: 0.691416\n",
      "[4]\tvalid_0's l1: 0.498429\tvalid_0's binary_logloss: 0.690626\n",
      "[5]\tvalid_0's l1: 0.497793\tvalid_0's binary_logloss: 0.689541\n",
      "[6]\tvalid_0's l1: 0.497428\tvalid_0's binary_logloss: 0.688836\n",
      "[7]\tvalid_0's l1: 0.497053\tvalid_0's binary_logloss: 0.688041\n",
      "[8]\tvalid_0's l1: 0.496404\tvalid_0's binary_logloss: 0.687094\n",
      "[9]\tvalid_0's l1: 0.495943\tvalid_0's binary_logloss: 0.686418\n",
      "[10]\tvalid_0's l1: 0.495967\tvalid_0's binary_logloss: 0.686723\n",
      "[11]\tvalid_0's l1: 0.495192\tvalid_0's binary_logloss: 0.685508\n",
      "[12]\tvalid_0's l1: 0.494522\tvalid_0's binary_logloss: 0.684252\n",
      "[13]\tvalid_0's l1: 0.49417\tvalid_0's binary_logloss: 0.683861\n",
      "[14]\tvalid_0's l1: 0.494106\tvalid_0's binary_logloss: 0.68389\n",
      "[15]\tvalid_0's l1: 0.493531\tvalid_0's binary_logloss: 0.683348\n",
      "[16]\tvalid_0's l1: 0.492902\tvalid_0's binary_logloss: 0.682188\n",
      "[17]\tvalid_0's l1: 0.49236\tvalid_0's binary_logloss: 0.681809\n",
      "[18]\tvalid_0's l1: 0.49202\tvalid_0's binary_logloss: 0.681469\n",
      "[19]\tvalid_0's l1: 0.491816\tvalid_0's binary_logloss: 0.681272\n",
      "[20]\tvalid_0's l1: 0.491805\tvalid_0's binary_logloss: 0.681266\n",
      "[21]\tvalid_0's l1: 0.491494\tvalid_0's binary_logloss: 0.681037\n",
      "[22]\tvalid_0's l1: 0.491499\tvalid_0's binary_logloss: 0.681305\n",
      "[23]\tvalid_0's l1: 0.490849\tvalid_0's binary_logloss: 0.68063\n",
      "[24]\tvalid_0's l1: 0.490614\tvalid_0's binary_logloss: 0.68047\n",
      "[25]\tvalid_0's l1: 0.490417\tvalid_0's binary_logloss: 0.680062\n",
      "[26]\tvalid_0's l1: 0.49019\tvalid_0's binary_logloss: 0.680045\n",
      "[27]\tvalid_0's l1: 0.489578\tvalid_0's binary_logloss: 0.678968\n",
      "[28]\tvalid_0's l1: 0.489047\tvalid_0's binary_logloss: 0.678065\n",
      "[29]\tvalid_0's l1: 0.488772\tvalid_0's binary_logloss: 0.677937\n",
      "[30]\tvalid_0's l1: 0.488467\tvalid_0's binary_logloss: 0.677877\n",
      "[31]\tvalid_0's l1: 0.487583\tvalid_0's binary_logloss: 0.676103\n",
      "[32]\tvalid_0's l1: 0.486885\tvalid_0's binary_logloss: 0.674837\n",
      "[33]\tvalid_0's l1: 0.486682\tvalid_0's binary_logloss: 0.674775\n",
      "[34]\tvalid_0's l1: 0.486224\tvalid_0's binary_logloss: 0.674534\n",
      "[35]\tvalid_0's l1: 0.486069\tvalid_0's binary_logloss: 0.67462\n",
      "[36]\tvalid_0's l1: 0.486062\tvalid_0's binary_logloss: 0.674633\n",
      "[37]\tvalid_0's l1: 0.485946\tvalid_0's binary_logloss: 0.674186\n",
      "[38]\tvalid_0's l1: 0.485815\tvalid_0's binary_logloss: 0.674324\n",
      "[39]\tvalid_0's l1: 0.485263\tvalid_0's binary_logloss: 0.673945\n",
      "[40]\tvalid_0's l1: 0.485292\tvalid_0's binary_logloss: 0.674229\n",
      "[41]\tvalid_0's l1: 0.48557\tvalid_0's binary_logloss: 0.674776\n",
      "[42]\tvalid_0's l1: 0.48556\tvalid_0's binary_logloss: 0.674817\n",
      "[43]\tvalid_0's l1: 0.485295\tvalid_0's binary_logloss: 0.674401\n",
      "[44]\tvalid_0's l1: 0.485186\tvalid_0's binary_logloss: 0.673987\n",
      "Early stopping, best iteration is:\n",
      "[39]\tvalid_0's l1: 0.485263\tvalid_0's binary_logloss: 0.673945\n",
      "[1]\tvalid_0's l1: 0.500631\tvalid_0's binary_logloss: 0.694891\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500818\tvalid_0's binary_logloss: 0.695295\n",
      "[3]\tvalid_0's l1: 0.500916\tvalid_0's binary_logloss: 0.695609\n",
      "[4]\tvalid_0's l1: 0.500713\tvalid_0's binary_logloss: 0.695268\n",
      "[5]\tvalid_0's l1: 0.500844\tvalid_0's binary_logloss: 0.695611\n",
      "[6]\tvalid_0's l1: 0.500546\tvalid_0's binary_logloss: 0.695204\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l1: 0.500631\tvalid_0's binary_logloss: 0.694891\n",
      "[1]\tvalid_0's l1: 0.500616\tvalid_0's binary_logloss: 0.694936\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500514\tvalid_0's binary_logloss: 0.694931\n",
      "[3]\tvalid_0's l1: 0.499897\tvalid_0's binary_logloss: 0.694146\n",
      "[4]\tvalid_0's l1: 0.4998\tvalid_0's binary_logloss: 0.694404\n",
      "[5]\tvalid_0's l1: 0.500325\tvalid_0's binary_logloss: 0.695595\n",
      "[6]\tvalid_0's l1: 0.500239\tvalid_0's binary_logloss: 0.695985\n",
      "[7]\tvalid_0's l1: 0.500347\tvalid_0's binary_logloss: 0.696931\n",
      "[8]\tvalid_0's l1: 0.499872\tvalid_0's binary_logloss: 0.696682\n",
      "Early stopping, best iteration is:\n",
      "[3]\tvalid_0's l1: 0.499897\tvalid_0's binary_logloss: 0.694146\n",
      "[1]\tvalid_0's l1: 0.500576\tvalid_0's binary_logloss: 0.694971\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500096\tvalid_0's binary_logloss: 0.694222\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3]\tvalid_0's l1: 0.499463\tvalid_0's binary_logloss: 0.693457\n",
      "[4]\tvalid_0's l1: 0.498895\tvalid_0's binary_logloss: 0.693017\n",
      "[5]\tvalid_0's l1: 0.498289\tvalid_0's binary_logloss: 0.691866\n",
      "[6]\tvalid_0's l1: 0.498219\tvalid_0's binary_logloss: 0.692466\n",
      "[7]\tvalid_0's l1: 0.497659\tvalid_0's binary_logloss: 0.691796\n",
      "[8]\tvalid_0's l1: 0.497335\tvalid_0's binary_logloss: 0.691477\n",
      "[9]\tvalid_0's l1: 0.49625\tvalid_0's binary_logloss: 0.6894\n",
      "[10]\tvalid_0's l1: 0.495711\tvalid_0's binary_logloss: 0.688965\n",
      "[11]\tvalid_0's l1: 0.495213\tvalid_0's binary_logloss: 0.688901\n",
      "[12]\tvalid_0's l1: 0.494197\tvalid_0's binary_logloss: 0.687147\n",
      "[13]\tvalid_0's l1: 0.493689\tvalid_0's binary_logloss: 0.686774\n",
      "[14]\tvalid_0's l1: 0.493395\tvalid_0's binary_logloss: 0.687032\n",
      "[15]\tvalid_0's l1: 0.493841\tvalid_0's binary_logloss: 0.688205\n",
      "[16]\tvalid_0's l1: 0.49348\tvalid_0's binary_logloss: 0.688234\n",
      "[17]\tvalid_0's l1: 0.493117\tvalid_0's binary_logloss: 0.688097\n",
      "[18]\tvalid_0's l1: 0.493086\tvalid_0's binary_logloss: 0.689305\n",
      "Early stopping, best iteration is:\n",
      "[13]\tvalid_0's l1: 0.493689\tvalid_0's binary_logloss: 0.686774\n",
      "[1]\tvalid_0's l1: 0.500737\tvalid_0's binary_logloss: 0.695564\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.50032\tvalid_0's binary_logloss: 0.695191\n",
      "[3]\tvalid_0's l1: 0.49986\tvalid_0's binary_logloss: 0.694458\n",
      "[4]\tvalid_0's l1: 0.499483\tvalid_0's binary_logloss: 0.694457\n",
      "[5]\tvalid_0's l1: 0.498573\tvalid_0's binary_logloss: 0.692991\n",
      "[6]\tvalid_0's l1: 0.497851\tvalid_0's binary_logloss: 0.692124\n",
      "[7]\tvalid_0's l1: 0.497249\tvalid_0's binary_logloss: 0.691707\n",
      "[8]\tvalid_0's l1: 0.496735\tvalid_0's binary_logloss: 0.691526\n",
      "[9]\tvalid_0's l1: 0.496471\tvalid_0's binary_logloss: 0.692091\n",
      "[10]\tvalid_0's l1: 0.495847\tvalid_0's binary_logloss: 0.691747\n",
      "[11]\tvalid_0's l1: 0.495218\tvalid_0's binary_logloss: 0.691623\n",
      "[12]\tvalid_0's l1: 0.494414\tvalid_0's binary_logloss: 0.691076\n",
      "[13]\tvalid_0's l1: 0.493534\tvalid_0's binary_logloss: 0.689988\n",
      "[14]\tvalid_0's l1: 0.493393\tvalid_0's binary_logloss: 0.6898\n",
      "[15]\tvalid_0's l1: 0.493202\tvalid_0's binary_logloss: 0.69115\n",
      "[16]\tvalid_0's l1: 0.492078\tvalid_0's binary_logloss: 0.689618\n",
      "[17]\tvalid_0's l1: 0.491836\tvalid_0's binary_logloss: 0.689047\n",
      "[18]\tvalid_0's l1: 0.491683\tvalid_0's binary_logloss: 0.689397\n",
      "[19]\tvalid_0's l1: 0.491248\tvalid_0's binary_logloss: 0.69008\n",
      "[20]\tvalid_0's l1: 0.49089\tvalid_0's binary_logloss: 0.690189\n",
      "[21]\tvalid_0's l1: 0.490649\tvalid_0's binary_logloss: 0.690408\n",
      "[22]\tvalid_0's l1: 0.490411\tvalid_0's binary_logloss: 0.690084\n",
      "Early stopping, best iteration is:\n",
      "[17]\tvalid_0's l1: 0.491836\tvalid_0's binary_logloss: 0.689047\n",
      "[1]\tvalid_0's l1: 0.500822\tvalid_0's binary_logloss: 0.695351\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500029\tvalid_0's binary_logloss: 0.693687\n",
      "[3]\tvalid_0's l1: 0.498879\tvalid_0's binary_logloss: 0.691416\n",
      "[4]\tvalid_0's l1: 0.498429\tvalid_0's binary_logloss: 0.690626\n",
      "[5]\tvalid_0's l1: 0.497793\tvalid_0's binary_logloss: 0.689541\n",
      "[6]\tvalid_0's l1: 0.497428\tvalid_0's binary_logloss: 0.688836\n",
      "[7]\tvalid_0's l1: 0.497053\tvalid_0's binary_logloss: 0.688041\n",
      "[8]\tvalid_0's l1: 0.496404\tvalid_0's binary_logloss: 0.687094\n",
      "[9]\tvalid_0's l1: 0.495943\tvalid_0's binary_logloss: 0.686418\n",
      "[10]\tvalid_0's l1: 0.495967\tvalid_0's binary_logloss: 0.686723\n",
      "[11]\tvalid_0's l1: 0.495192\tvalid_0's binary_logloss: 0.685508\n",
      "[12]\tvalid_0's l1: 0.494522\tvalid_0's binary_logloss: 0.684252\n",
      "[13]\tvalid_0's l1: 0.49417\tvalid_0's binary_logloss: 0.683861\n",
      "[14]\tvalid_0's l1: 0.494106\tvalid_0's binary_logloss: 0.68389\n",
      "[15]\tvalid_0's l1: 0.493531\tvalid_0's binary_logloss: 0.683348\n",
      "[16]\tvalid_0's l1: 0.492902\tvalid_0's binary_logloss: 0.682188\n",
      "[17]\tvalid_0's l1: 0.49236\tvalid_0's binary_logloss: 0.681809\n",
      "[18]\tvalid_0's l1: 0.49202\tvalid_0's binary_logloss: 0.681469\n",
      "[19]\tvalid_0's l1: 0.491816\tvalid_0's binary_logloss: 0.681272\n",
      "[20]\tvalid_0's l1: 0.491805\tvalid_0's binary_logloss: 0.681266\n",
      "[21]\tvalid_0's l1: 0.491494\tvalid_0's binary_logloss: 0.681037\n",
      "[22]\tvalid_0's l1: 0.491499\tvalid_0's binary_logloss: 0.681305\n",
      "[23]\tvalid_0's l1: 0.490849\tvalid_0's binary_logloss: 0.68063\n",
      "[24]\tvalid_0's l1: 0.490614\tvalid_0's binary_logloss: 0.68047\n",
      "[25]\tvalid_0's l1: 0.490417\tvalid_0's binary_logloss: 0.680062\n",
      "[26]\tvalid_0's l1: 0.49019\tvalid_0's binary_logloss: 0.680045\n",
      "[27]\tvalid_0's l1: 0.489578\tvalid_0's binary_logloss: 0.678968\n",
      "[28]\tvalid_0's l1: 0.489047\tvalid_0's binary_logloss: 0.678065\n",
      "[29]\tvalid_0's l1: 0.488772\tvalid_0's binary_logloss: 0.677937\n",
      "[30]\tvalid_0's l1: 0.488467\tvalid_0's binary_logloss: 0.677877\n",
      "[31]\tvalid_0's l1: 0.487583\tvalid_0's binary_logloss: 0.676103\n",
      "[32]\tvalid_0's l1: 0.486885\tvalid_0's binary_logloss: 0.674837\n",
      "[33]\tvalid_0's l1: 0.486682\tvalid_0's binary_logloss: 0.674775\n",
      "[34]\tvalid_0's l1: 0.486224\tvalid_0's binary_logloss: 0.674534\n",
      "[35]\tvalid_0's l1: 0.486069\tvalid_0's binary_logloss: 0.67462\n",
      "[36]\tvalid_0's l1: 0.486062\tvalid_0's binary_logloss: 0.674633\n",
      "[37]\tvalid_0's l1: 0.485946\tvalid_0's binary_logloss: 0.674186\n",
      "[38]\tvalid_0's l1: 0.485815\tvalid_0's binary_logloss: 0.674324\n",
      "[39]\tvalid_0's l1: 0.485263\tvalid_0's binary_logloss: 0.673945\n",
      "[40]\tvalid_0's l1: 0.485292\tvalid_0's binary_logloss: 0.674229\n",
      "[41]\tvalid_0's l1: 0.48557\tvalid_0's binary_logloss: 0.674776\n",
      "[42]\tvalid_0's l1: 0.48556\tvalid_0's binary_logloss: 0.674817\n",
      "[43]\tvalid_0's l1: 0.485295\tvalid_0's binary_logloss: 0.674401\n",
      "[44]\tvalid_0's l1: 0.485186\tvalid_0's binary_logloss: 0.673987\n",
      "Early stopping, best iteration is:\n",
      "[39]\tvalid_0's l1: 0.485263\tvalid_0's binary_logloss: 0.673945\n",
      "[1]\tvalid_0's l1: 0.500631\tvalid_0's binary_logloss: 0.694891\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500818\tvalid_0's binary_logloss: 0.695295\n",
      "[3]\tvalid_0's l1: 0.500916\tvalid_0's binary_logloss: 0.695609\n",
      "[4]\tvalid_0's l1: 0.500713\tvalid_0's binary_logloss: 0.695268\n",
      "[5]\tvalid_0's l1: 0.500844\tvalid_0's binary_logloss: 0.695611\n",
      "[6]\tvalid_0's l1: 0.500546\tvalid_0's binary_logloss: 0.695204\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l1: 0.500631\tvalid_0's binary_logloss: 0.694891\n",
      "[1]\tvalid_0's l1: 0.500616\tvalid_0's binary_logloss: 0.694936\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500514\tvalid_0's binary_logloss: 0.694931\n",
      "[3]\tvalid_0's l1: 0.499897\tvalid_0's binary_logloss: 0.694146\n",
      "[4]\tvalid_0's l1: 0.4998\tvalid_0's binary_logloss: 0.694404\n",
      "[5]\tvalid_0's l1: 0.500325\tvalid_0's binary_logloss: 0.695595\n",
      "[6]\tvalid_0's l1: 0.500239\tvalid_0's binary_logloss: 0.695985\n",
      "[7]\tvalid_0's l1: 0.500347\tvalid_0's binary_logloss: 0.696931\n",
      "[8]\tvalid_0's l1: 0.499872\tvalid_0's binary_logloss: 0.696682\n",
      "Early stopping, best iteration is:\n",
      "[3]\tvalid_0's l1: 0.499897\tvalid_0's binary_logloss: 0.694146\n",
      "[1]\tvalid_0's l1: 0.500576\tvalid_0's binary_logloss: 0.694971\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500096\tvalid_0's binary_logloss: 0.694222\n",
      "[3]\tvalid_0's l1: 0.499463\tvalid_0's binary_logloss: 0.693457\n",
      "[4]\tvalid_0's l1: 0.498895\tvalid_0's binary_logloss: 0.693017\n",
      "[5]\tvalid_0's l1: 0.498289\tvalid_0's binary_logloss: 0.691866\n",
      "[6]\tvalid_0's l1: 0.498219\tvalid_0's binary_logloss: 0.692466\n",
      "[7]\tvalid_0's l1: 0.497659\tvalid_0's binary_logloss: 0.691796\n",
      "[8]\tvalid_0's l1: 0.497335\tvalid_0's binary_logloss: 0.691477\n",
      "[9]\tvalid_0's l1: 0.49625\tvalid_0's binary_logloss: 0.6894\n",
      "[10]\tvalid_0's l1: 0.495711\tvalid_0's binary_logloss: 0.688965\n",
      "[11]\tvalid_0's l1: 0.495213\tvalid_0's binary_logloss: 0.688901\n",
      "[12]\tvalid_0's l1: 0.494197\tvalid_0's binary_logloss: 0.687147\n",
      "[13]\tvalid_0's l1: 0.493689\tvalid_0's binary_logloss: 0.686774\n",
      "[14]\tvalid_0's l1: 0.493395\tvalid_0's binary_logloss: 0.687032\n",
      "[15]\tvalid_0's l1: 0.493841\tvalid_0's binary_logloss: 0.688205\n",
      "[16]\tvalid_0's l1: 0.49348\tvalid_0's binary_logloss: 0.688234\n",
      "[17]\tvalid_0's l1: 0.493117\tvalid_0's binary_logloss: 0.688097\n",
      "[18]\tvalid_0's l1: 0.493086\tvalid_0's binary_logloss: 0.689305\n",
      "Early stopping, best iteration is:\n",
      "[13]\tvalid_0's l1: 0.493689\tvalid_0's binary_logloss: 0.686774\n",
      "[1]\tvalid_0's l1: 0.500737\tvalid_0's binary_logloss: 0.695564\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.50032\tvalid_0's binary_logloss: 0.695191\n",
      "[3]\tvalid_0's l1: 0.49986\tvalid_0's binary_logloss: 0.694458\n",
      "[4]\tvalid_0's l1: 0.499483\tvalid_0's binary_logloss: 0.694457\n",
      "[5]\tvalid_0's l1: 0.498573\tvalid_0's binary_logloss: 0.692991\n",
      "[6]\tvalid_0's l1: 0.497851\tvalid_0's binary_logloss: 0.692124\n",
      "[7]\tvalid_0's l1: 0.497249\tvalid_0's binary_logloss: 0.691707\n",
      "[8]\tvalid_0's l1: 0.496735\tvalid_0's binary_logloss: 0.691526\n",
      "[9]\tvalid_0's l1: 0.496471\tvalid_0's binary_logloss: 0.692091\n",
      "[10]\tvalid_0's l1: 0.495847\tvalid_0's binary_logloss: 0.691747\n",
      "[11]\tvalid_0's l1: 0.495218\tvalid_0's binary_logloss: 0.691623\n",
      "[12]\tvalid_0's l1: 0.494414\tvalid_0's binary_logloss: 0.691076\n",
      "[13]\tvalid_0's l1: 0.493534\tvalid_0's binary_logloss: 0.689988\n",
      "[14]\tvalid_0's l1: 0.493393\tvalid_0's binary_logloss: 0.6898\n",
      "[15]\tvalid_0's l1: 0.493202\tvalid_0's binary_logloss: 0.69115\n",
      "[16]\tvalid_0's l1: 0.492078\tvalid_0's binary_logloss: 0.689618\n",
      "[17]\tvalid_0's l1: 0.491836\tvalid_0's binary_logloss: 0.689047\n",
      "[18]\tvalid_0's l1: 0.491683\tvalid_0's binary_logloss: 0.689397\n",
      "[19]\tvalid_0's l1: 0.491248\tvalid_0's binary_logloss: 0.69008\n",
      "[20]\tvalid_0's l1: 0.49089\tvalid_0's binary_logloss: 0.690189\n",
      "[21]\tvalid_0's l1: 0.490649\tvalid_0's binary_logloss: 0.690408\n",
      "[22]\tvalid_0's l1: 0.490411\tvalid_0's binary_logloss: 0.690084\n",
      "Early stopping, best iteration is:\n",
      "[17]\tvalid_0's l1: 0.491836\tvalid_0's binary_logloss: 0.689047\n",
      "[1]\tvalid_0's l1: 0.500822\tvalid_0's binary_logloss: 0.695351\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500029\tvalid_0's binary_logloss: 0.693687\n",
      "[3]\tvalid_0's l1: 0.498879\tvalid_0's binary_logloss: 0.691416\n",
      "[4]\tvalid_0's l1: 0.498429\tvalid_0's binary_logloss: 0.690626\n",
      "[5]\tvalid_0's l1: 0.497793\tvalid_0's binary_logloss: 0.689541\n",
      "[6]\tvalid_0's l1: 0.497428\tvalid_0's binary_logloss: 0.688836\n",
      "[7]\tvalid_0's l1: 0.497053\tvalid_0's binary_logloss: 0.688041\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[8]\tvalid_0's l1: 0.496404\tvalid_0's binary_logloss: 0.687094\n",
      "[9]\tvalid_0's l1: 0.495943\tvalid_0's binary_logloss: 0.686418\n",
      "[10]\tvalid_0's l1: 0.495967\tvalid_0's binary_logloss: 0.686723\n",
      "[11]\tvalid_0's l1: 0.495192\tvalid_0's binary_logloss: 0.685508\n",
      "[12]\tvalid_0's l1: 0.494522\tvalid_0's binary_logloss: 0.684252\n",
      "[13]\tvalid_0's l1: 0.49417\tvalid_0's binary_logloss: 0.683861\n",
      "[14]\tvalid_0's l1: 0.494106\tvalid_0's binary_logloss: 0.68389\n",
      "[15]\tvalid_0's l1: 0.493531\tvalid_0's binary_logloss: 0.683348\n",
      "[16]\tvalid_0's l1: 0.492902\tvalid_0's binary_logloss: 0.682188\n",
      "[17]\tvalid_0's l1: 0.49236\tvalid_0's binary_logloss: 0.681809\n",
      "[18]\tvalid_0's l1: 0.49202\tvalid_0's binary_logloss: 0.681469\n",
      "[19]\tvalid_0's l1: 0.491816\tvalid_0's binary_logloss: 0.681272\n",
      "[20]\tvalid_0's l1: 0.491805\tvalid_0's binary_logloss: 0.681266\n",
      "[21]\tvalid_0's l1: 0.491494\tvalid_0's binary_logloss: 0.681037\n",
      "[22]\tvalid_0's l1: 0.491499\tvalid_0's binary_logloss: 0.681305\n",
      "[23]\tvalid_0's l1: 0.490849\tvalid_0's binary_logloss: 0.68063\n",
      "[24]\tvalid_0's l1: 0.490614\tvalid_0's binary_logloss: 0.68047\n",
      "[25]\tvalid_0's l1: 0.490417\tvalid_0's binary_logloss: 0.680062\n",
      "[26]\tvalid_0's l1: 0.49019\tvalid_0's binary_logloss: 0.680045\n",
      "[27]\tvalid_0's l1: 0.489578\tvalid_0's binary_logloss: 0.678968\n",
      "[28]\tvalid_0's l1: 0.489047\tvalid_0's binary_logloss: 0.678065\n",
      "[29]\tvalid_0's l1: 0.488772\tvalid_0's binary_logloss: 0.677937\n",
      "[30]\tvalid_0's l1: 0.488467\tvalid_0's binary_logloss: 0.677877\n",
      "[31]\tvalid_0's l1: 0.487583\tvalid_0's binary_logloss: 0.676103\n",
      "[32]\tvalid_0's l1: 0.486885\tvalid_0's binary_logloss: 0.674837\n",
      "[33]\tvalid_0's l1: 0.486682\tvalid_0's binary_logloss: 0.674775\n",
      "[34]\tvalid_0's l1: 0.486224\tvalid_0's binary_logloss: 0.674534\n",
      "[35]\tvalid_0's l1: 0.486069\tvalid_0's binary_logloss: 0.67462\n",
      "[36]\tvalid_0's l1: 0.486062\tvalid_0's binary_logloss: 0.674633\n",
      "[37]\tvalid_0's l1: 0.485946\tvalid_0's binary_logloss: 0.674186\n",
      "[38]\tvalid_0's l1: 0.485815\tvalid_0's binary_logloss: 0.674324\n",
      "[39]\tvalid_0's l1: 0.485263\tvalid_0's binary_logloss: 0.673945\n",
      "[40]\tvalid_0's l1: 0.485292\tvalid_0's binary_logloss: 0.674229\n",
      "[41]\tvalid_0's l1: 0.48557\tvalid_0's binary_logloss: 0.674776\n",
      "[42]\tvalid_0's l1: 0.48556\tvalid_0's binary_logloss: 0.674817\n",
      "[43]\tvalid_0's l1: 0.485295\tvalid_0's binary_logloss: 0.674401\n",
      "[44]\tvalid_0's l1: 0.485186\tvalid_0's binary_logloss: 0.673987\n",
      "Early stopping, best iteration is:\n",
      "[39]\tvalid_0's l1: 0.485263\tvalid_0's binary_logloss: 0.673945\n",
      "[1]\tvalid_0's l1: 0.500631\tvalid_0's binary_logloss: 0.694891\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500818\tvalid_0's binary_logloss: 0.695295\n",
      "[3]\tvalid_0's l1: 0.500916\tvalid_0's binary_logloss: 0.695609\n",
      "[4]\tvalid_0's l1: 0.500713\tvalid_0's binary_logloss: 0.695268\n",
      "[5]\tvalid_0's l1: 0.500844\tvalid_0's binary_logloss: 0.695611\n",
      "[6]\tvalid_0's l1: 0.500546\tvalid_0's binary_logloss: 0.695204\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l1: 0.500631\tvalid_0's binary_logloss: 0.694891\n",
      "[1]\tvalid_0's l1: 0.500616\tvalid_0's binary_logloss: 0.694936\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500514\tvalid_0's binary_logloss: 0.694931\n",
      "[3]\tvalid_0's l1: 0.499897\tvalid_0's binary_logloss: 0.694146\n",
      "[4]\tvalid_0's l1: 0.4998\tvalid_0's binary_logloss: 0.694404\n",
      "[5]\tvalid_0's l1: 0.500325\tvalid_0's binary_logloss: 0.695595\n",
      "[6]\tvalid_0's l1: 0.500239\tvalid_0's binary_logloss: 0.695985\n",
      "[7]\tvalid_0's l1: 0.500347\tvalid_0's binary_logloss: 0.696931\n",
      "[8]\tvalid_0's l1: 0.499872\tvalid_0's binary_logloss: 0.696682\n",
      "Early stopping, best iteration is:\n",
      "[3]\tvalid_0's l1: 0.499897\tvalid_0's binary_logloss: 0.694146\n",
      "[1]\tvalid_0's l1: 0.500576\tvalid_0's binary_logloss: 0.694971\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500096\tvalid_0's binary_logloss: 0.694222\n",
      "[3]\tvalid_0's l1: 0.499463\tvalid_0's binary_logloss: 0.693457\n",
      "[4]\tvalid_0's l1: 0.498895\tvalid_0's binary_logloss: 0.693017\n",
      "[5]\tvalid_0's l1: 0.498289\tvalid_0's binary_logloss: 0.691866\n",
      "[6]\tvalid_0's l1: 0.498219\tvalid_0's binary_logloss: 0.692466\n",
      "[7]\tvalid_0's l1: 0.497659\tvalid_0's binary_logloss: 0.691796\n",
      "[8]\tvalid_0's l1: 0.497335\tvalid_0's binary_logloss: 0.691477\n",
      "[9]\tvalid_0's l1: 0.49625\tvalid_0's binary_logloss: 0.6894\n",
      "[10]\tvalid_0's l1: 0.495711\tvalid_0's binary_logloss: 0.688965\n",
      "[11]\tvalid_0's l1: 0.495213\tvalid_0's binary_logloss: 0.688901\n",
      "[12]\tvalid_0's l1: 0.494197\tvalid_0's binary_logloss: 0.687147\n",
      "[13]\tvalid_0's l1: 0.493689\tvalid_0's binary_logloss: 0.686774\n",
      "[14]\tvalid_0's l1: 0.493395\tvalid_0's binary_logloss: 0.687032\n",
      "[15]\tvalid_0's l1: 0.493841\tvalid_0's binary_logloss: 0.688205\n",
      "[16]\tvalid_0's l1: 0.49348\tvalid_0's binary_logloss: 0.688234\n",
      "[17]\tvalid_0's l1: 0.493117\tvalid_0's binary_logloss: 0.688097\n",
      "[18]\tvalid_0's l1: 0.493086\tvalid_0's binary_logloss: 0.689305\n",
      "Early stopping, best iteration is:\n",
      "[13]\tvalid_0's l1: 0.493689\tvalid_0's binary_logloss: 0.686774\n",
      "[1]\tvalid_0's l1: 0.500737\tvalid_0's binary_logloss: 0.695564\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.50032\tvalid_0's binary_logloss: 0.695191\n",
      "[3]\tvalid_0's l1: 0.49986\tvalid_0's binary_logloss: 0.694458\n",
      "[4]\tvalid_0's l1: 0.499483\tvalid_0's binary_logloss: 0.694457\n",
      "[5]\tvalid_0's l1: 0.498573\tvalid_0's binary_logloss: 0.692991\n",
      "[6]\tvalid_0's l1: 0.497851\tvalid_0's binary_logloss: 0.692124\n",
      "[7]\tvalid_0's l1: 0.497249\tvalid_0's binary_logloss: 0.691707\n",
      "[8]\tvalid_0's l1: 0.496735\tvalid_0's binary_logloss: 0.691526\n",
      "[9]\tvalid_0's l1: 0.496471\tvalid_0's binary_logloss: 0.692091\n",
      "[10]\tvalid_0's l1: 0.495847\tvalid_0's binary_logloss: 0.691747\n",
      "[11]\tvalid_0's l1: 0.495218\tvalid_0's binary_logloss: 0.691623\n",
      "[12]\tvalid_0's l1: 0.494414\tvalid_0's binary_logloss: 0.691076\n",
      "[13]\tvalid_0's l1: 0.493534\tvalid_0's binary_logloss: 0.689988\n",
      "[14]\tvalid_0's l1: 0.493393\tvalid_0's binary_logloss: 0.6898\n",
      "[15]\tvalid_0's l1: 0.493202\tvalid_0's binary_logloss: 0.69115\n",
      "[16]\tvalid_0's l1: 0.492078\tvalid_0's binary_logloss: 0.689618\n",
      "[17]\tvalid_0's l1: 0.491836\tvalid_0's binary_logloss: 0.689047\n",
      "[18]\tvalid_0's l1: 0.491683\tvalid_0's binary_logloss: 0.689397\n",
      "[19]\tvalid_0's l1: 0.491248\tvalid_0's binary_logloss: 0.69008\n",
      "[20]\tvalid_0's l1: 0.49089\tvalid_0's binary_logloss: 0.690189\n",
      "[21]\tvalid_0's l1: 0.490649\tvalid_0's binary_logloss: 0.690408\n",
      "[22]\tvalid_0's l1: 0.490411\tvalid_0's binary_logloss: 0.690084\n",
      "Early stopping, best iteration is:\n",
      "[17]\tvalid_0's l1: 0.491836\tvalid_0's binary_logloss: 0.689047\n",
      "[1]\tvalid_0's l1: 0.500822\tvalid_0's binary_logloss: 0.695351\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500029\tvalid_0's binary_logloss: 0.693687\n",
      "[3]\tvalid_0's l1: 0.498879\tvalid_0's binary_logloss: 0.691416\n",
      "[4]\tvalid_0's l1: 0.498429\tvalid_0's binary_logloss: 0.690626\n",
      "[5]\tvalid_0's l1: 0.497793\tvalid_0's binary_logloss: 0.689541\n",
      "[6]\tvalid_0's l1: 0.497428\tvalid_0's binary_logloss: 0.688836\n",
      "[7]\tvalid_0's l1: 0.497053\tvalid_0's binary_logloss: 0.688041\n",
      "[8]\tvalid_0's l1: 0.496404\tvalid_0's binary_logloss: 0.687094\n",
      "[9]\tvalid_0's l1: 0.495943\tvalid_0's binary_logloss: 0.686418\n",
      "[10]\tvalid_0's l1: 0.495967\tvalid_0's binary_logloss: 0.686723\n",
      "[11]\tvalid_0's l1: 0.495192\tvalid_0's binary_logloss: 0.685508\n",
      "[12]\tvalid_0's l1: 0.494522\tvalid_0's binary_logloss: 0.684252\n",
      "[13]\tvalid_0's l1: 0.49417\tvalid_0's binary_logloss: 0.683861\n",
      "[14]\tvalid_0's l1: 0.494106\tvalid_0's binary_logloss: 0.68389\n",
      "[15]\tvalid_0's l1: 0.493531\tvalid_0's binary_logloss: 0.683348\n",
      "[16]\tvalid_0's l1: 0.492902\tvalid_0's binary_logloss: 0.682188\n",
      "[17]\tvalid_0's l1: 0.49236\tvalid_0's binary_logloss: 0.681809\n",
      "[18]\tvalid_0's l1: 0.49202\tvalid_0's binary_logloss: 0.681469\n",
      "[19]\tvalid_0's l1: 0.491816\tvalid_0's binary_logloss: 0.681272\n",
      "[20]\tvalid_0's l1: 0.491805\tvalid_0's binary_logloss: 0.681266\n",
      "[21]\tvalid_0's l1: 0.491494\tvalid_0's binary_logloss: 0.681037\n",
      "[22]\tvalid_0's l1: 0.491499\tvalid_0's binary_logloss: 0.681305\n",
      "[23]\tvalid_0's l1: 0.490849\tvalid_0's binary_logloss: 0.68063\n",
      "[24]\tvalid_0's l1: 0.490614\tvalid_0's binary_logloss: 0.68047\n",
      "[25]\tvalid_0's l1: 0.490417\tvalid_0's binary_logloss: 0.680062\n",
      "[26]\tvalid_0's l1: 0.49019\tvalid_0's binary_logloss: 0.680045\n",
      "[27]\tvalid_0's l1: 0.489578\tvalid_0's binary_logloss: 0.678968\n",
      "[28]\tvalid_0's l1: 0.489047\tvalid_0's binary_logloss: 0.678065\n",
      "[29]\tvalid_0's l1: 0.488772\tvalid_0's binary_logloss: 0.677937\n",
      "[30]\tvalid_0's l1: 0.488467\tvalid_0's binary_logloss: 0.677877\n",
      "[31]\tvalid_0's l1: 0.487583\tvalid_0's binary_logloss: 0.676103\n",
      "[32]\tvalid_0's l1: 0.486885\tvalid_0's binary_logloss: 0.674837\n",
      "[33]\tvalid_0's l1: 0.486682\tvalid_0's binary_logloss: 0.674775\n",
      "[34]\tvalid_0's l1: 0.486224\tvalid_0's binary_logloss: 0.674534\n",
      "[35]\tvalid_0's l1: 0.486069\tvalid_0's binary_logloss: 0.67462\n",
      "[36]\tvalid_0's l1: 0.486062\tvalid_0's binary_logloss: 0.674633\n",
      "[37]\tvalid_0's l1: 0.485946\tvalid_0's binary_logloss: 0.674186\n",
      "[38]\tvalid_0's l1: 0.485815\tvalid_0's binary_logloss: 0.674324\n",
      "[39]\tvalid_0's l1: 0.485263\tvalid_0's binary_logloss: 0.673945\n",
      "[40]\tvalid_0's l1: 0.485292\tvalid_0's binary_logloss: 0.674229\n",
      "[41]\tvalid_0's l1: 0.48557\tvalid_0's binary_logloss: 0.674776\n",
      "[42]\tvalid_0's l1: 0.48556\tvalid_0's binary_logloss: 0.674817\n",
      "[43]\tvalid_0's l1: 0.485295\tvalid_0's binary_logloss: 0.674401\n",
      "[44]\tvalid_0's l1: 0.485186\tvalid_0's binary_logloss: 0.673987\n",
      "Early stopping, best iteration is:\n",
      "[39]\tvalid_0's l1: 0.485263\tvalid_0's binary_logloss: 0.673945\n",
      "[1]\tvalid_0's l1: 0.500631\tvalid_0's binary_logloss: 0.694891\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500818\tvalid_0's binary_logloss: 0.695295\n",
      "[3]\tvalid_0's l1: 0.500916\tvalid_0's binary_logloss: 0.695609\n",
      "[4]\tvalid_0's l1: 0.500713\tvalid_0's binary_logloss: 0.695268\n",
      "[5]\tvalid_0's l1: 0.500844\tvalid_0's binary_logloss: 0.695611\n",
      "[6]\tvalid_0's l1: 0.500546\tvalid_0's binary_logloss: 0.695204\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l1: 0.500631\tvalid_0's binary_logloss: 0.694891\n",
      "[1]\tvalid_0's l1: 0.500616\tvalid_0's binary_logloss: 0.694936\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500514\tvalid_0's binary_logloss: 0.694931\n",
      "[3]\tvalid_0's l1: 0.499897\tvalid_0's binary_logloss: 0.694146\n",
      "[4]\tvalid_0's l1: 0.4998\tvalid_0's binary_logloss: 0.694404\n",
      "[5]\tvalid_0's l1: 0.500325\tvalid_0's binary_logloss: 0.695595\n",
      "[6]\tvalid_0's l1: 0.500239\tvalid_0's binary_logloss: 0.695985\n",
      "[7]\tvalid_0's l1: 0.500347\tvalid_0's binary_logloss: 0.696931\n",
      "[8]\tvalid_0's l1: 0.499872\tvalid_0's binary_logloss: 0.696682\n",
      "Early stopping, best iteration is:\n",
      "[3]\tvalid_0's l1: 0.499897\tvalid_0's binary_logloss: 0.694146\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1]\tvalid_0's l1: 0.500576\tvalid_0's binary_logloss: 0.694971\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500096\tvalid_0's binary_logloss: 0.694222\n",
      "[3]\tvalid_0's l1: 0.499463\tvalid_0's binary_logloss: 0.693457\n",
      "[4]\tvalid_0's l1: 0.498895\tvalid_0's binary_logloss: 0.693017\n",
      "[5]\tvalid_0's l1: 0.498289\tvalid_0's binary_logloss: 0.691866\n",
      "[6]\tvalid_0's l1: 0.498219\tvalid_0's binary_logloss: 0.692466\n",
      "[7]\tvalid_0's l1: 0.497659\tvalid_0's binary_logloss: 0.691796\n",
      "[8]\tvalid_0's l1: 0.497335\tvalid_0's binary_logloss: 0.691477\n",
      "[9]\tvalid_0's l1: 0.49625\tvalid_0's binary_logloss: 0.6894\n",
      "[10]\tvalid_0's l1: 0.495711\tvalid_0's binary_logloss: 0.688965\n",
      "[11]\tvalid_0's l1: 0.495213\tvalid_0's binary_logloss: 0.688901\n",
      "[12]\tvalid_0's l1: 0.494197\tvalid_0's binary_logloss: 0.687147\n",
      "[13]\tvalid_0's l1: 0.493689\tvalid_0's binary_logloss: 0.686774\n",
      "[14]\tvalid_0's l1: 0.493395\tvalid_0's binary_logloss: 0.687032\n",
      "[15]\tvalid_0's l1: 0.493841\tvalid_0's binary_logloss: 0.688205\n",
      "[16]\tvalid_0's l1: 0.49348\tvalid_0's binary_logloss: 0.688234\n",
      "[17]\tvalid_0's l1: 0.493117\tvalid_0's binary_logloss: 0.688097\n",
      "[18]\tvalid_0's l1: 0.493086\tvalid_0's binary_logloss: 0.689305\n",
      "Early stopping, best iteration is:\n",
      "[13]\tvalid_0's l1: 0.493689\tvalid_0's binary_logloss: 0.686774\n",
      "[1]\tvalid_0's l1: 0.500737\tvalid_0's binary_logloss: 0.695564\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.50032\tvalid_0's binary_logloss: 0.695191\n",
      "[3]\tvalid_0's l1: 0.49986\tvalid_0's binary_logloss: 0.694458\n",
      "[4]\tvalid_0's l1: 0.499483\tvalid_0's binary_logloss: 0.694457\n",
      "[5]\tvalid_0's l1: 0.498573\tvalid_0's binary_logloss: 0.692991\n",
      "[6]\tvalid_0's l1: 0.497851\tvalid_0's binary_logloss: 0.692124\n",
      "[7]\tvalid_0's l1: 0.497249\tvalid_0's binary_logloss: 0.691707\n",
      "[8]\tvalid_0's l1: 0.496735\tvalid_0's binary_logloss: 0.691526\n",
      "[9]\tvalid_0's l1: 0.496471\tvalid_0's binary_logloss: 0.692091\n",
      "[10]\tvalid_0's l1: 0.495847\tvalid_0's binary_logloss: 0.691747\n",
      "[11]\tvalid_0's l1: 0.495218\tvalid_0's binary_logloss: 0.691623\n",
      "[12]\tvalid_0's l1: 0.494414\tvalid_0's binary_logloss: 0.691076\n",
      "[13]\tvalid_0's l1: 0.493534\tvalid_0's binary_logloss: 0.689988\n",
      "[14]\tvalid_0's l1: 0.493393\tvalid_0's binary_logloss: 0.6898\n",
      "[15]\tvalid_0's l1: 0.493202\tvalid_0's binary_logloss: 0.69115\n",
      "[16]\tvalid_0's l1: 0.492078\tvalid_0's binary_logloss: 0.689618\n",
      "[17]\tvalid_0's l1: 0.491836\tvalid_0's binary_logloss: 0.689047\n",
      "[18]\tvalid_0's l1: 0.491683\tvalid_0's binary_logloss: 0.689397\n",
      "[19]\tvalid_0's l1: 0.491248\tvalid_0's binary_logloss: 0.69008\n",
      "[20]\tvalid_0's l1: 0.49089\tvalid_0's binary_logloss: 0.690189\n",
      "[21]\tvalid_0's l1: 0.490649\tvalid_0's binary_logloss: 0.690408\n",
      "[22]\tvalid_0's l1: 0.490411\tvalid_0's binary_logloss: 0.690084\n",
      "Early stopping, best iteration is:\n",
      "[17]\tvalid_0's l1: 0.491836\tvalid_0's binary_logloss: 0.689047\n",
      "[1]\tvalid_0's l1: 0.500822\tvalid_0's binary_logloss: 0.695351\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500029\tvalid_0's binary_logloss: 0.693687\n",
      "[3]\tvalid_0's l1: 0.498879\tvalid_0's binary_logloss: 0.691416\n",
      "[4]\tvalid_0's l1: 0.498429\tvalid_0's binary_logloss: 0.690626\n",
      "[5]\tvalid_0's l1: 0.497793\tvalid_0's binary_logloss: 0.689541\n",
      "[6]\tvalid_0's l1: 0.497428\tvalid_0's binary_logloss: 0.688836\n",
      "[7]\tvalid_0's l1: 0.497053\tvalid_0's binary_logloss: 0.688041\n",
      "[8]\tvalid_0's l1: 0.496404\tvalid_0's binary_logloss: 0.687094\n",
      "[9]\tvalid_0's l1: 0.495943\tvalid_0's binary_logloss: 0.686418\n",
      "[10]\tvalid_0's l1: 0.495967\tvalid_0's binary_logloss: 0.686723\n",
      "[11]\tvalid_0's l1: 0.495192\tvalid_0's binary_logloss: 0.685508\n",
      "[12]\tvalid_0's l1: 0.494522\tvalid_0's binary_logloss: 0.684252\n",
      "[13]\tvalid_0's l1: 0.49417\tvalid_0's binary_logloss: 0.683861\n",
      "[14]\tvalid_0's l1: 0.494106\tvalid_0's binary_logloss: 0.68389\n",
      "[15]\tvalid_0's l1: 0.493531\tvalid_0's binary_logloss: 0.683348\n",
      "[16]\tvalid_0's l1: 0.492902\tvalid_0's binary_logloss: 0.682188\n",
      "[17]\tvalid_0's l1: 0.49236\tvalid_0's binary_logloss: 0.681809\n",
      "[18]\tvalid_0's l1: 0.49202\tvalid_0's binary_logloss: 0.681469\n",
      "[19]\tvalid_0's l1: 0.491816\tvalid_0's binary_logloss: 0.681272\n",
      "[20]\tvalid_0's l1: 0.491805\tvalid_0's binary_logloss: 0.681266\n",
      "[21]\tvalid_0's l1: 0.491494\tvalid_0's binary_logloss: 0.681037\n",
      "[22]\tvalid_0's l1: 0.491499\tvalid_0's binary_logloss: 0.681305\n",
      "[23]\tvalid_0's l1: 0.490849\tvalid_0's binary_logloss: 0.68063\n",
      "[24]\tvalid_0's l1: 0.490614\tvalid_0's binary_logloss: 0.68047\n",
      "[25]\tvalid_0's l1: 0.490417\tvalid_0's binary_logloss: 0.680062\n",
      "[26]\tvalid_0's l1: 0.49019\tvalid_0's binary_logloss: 0.680045\n",
      "[27]\tvalid_0's l1: 0.489578\tvalid_0's binary_logloss: 0.678968\n",
      "[28]\tvalid_0's l1: 0.489047\tvalid_0's binary_logloss: 0.678065\n",
      "[29]\tvalid_0's l1: 0.488772\tvalid_0's binary_logloss: 0.677937\n",
      "[30]\tvalid_0's l1: 0.488467\tvalid_0's binary_logloss: 0.677877\n",
      "[31]\tvalid_0's l1: 0.487583\tvalid_0's binary_logloss: 0.676103\n",
      "[32]\tvalid_0's l1: 0.486885\tvalid_0's binary_logloss: 0.674837\n",
      "[33]\tvalid_0's l1: 0.486682\tvalid_0's binary_logloss: 0.674775\n",
      "[34]\tvalid_0's l1: 0.486224\tvalid_0's binary_logloss: 0.674534\n",
      "[35]\tvalid_0's l1: 0.486069\tvalid_0's binary_logloss: 0.67462\n",
      "[36]\tvalid_0's l1: 0.486062\tvalid_0's binary_logloss: 0.674633\n",
      "[37]\tvalid_0's l1: 0.485946\tvalid_0's binary_logloss: 0.674186\n",
      "[38]\tvalid_0's l1: 0.485815\tvalid_0's binary_logloss: 0.674324\n",
      "[39]\tvalid_0's l1: 0.485263\tvalid_0's binary_logloss: 0.673945\n",
      "[40]\tvalid_0's l1: 0.485292\tvalid_0's binary_logloss: 0.674229\n",
      "[41]\tvalid_0's l1: 0.48557\tvalid_0's binary_logloss: 0.674776\n",
      "[42]\tvalid_0's l1: 0.48556\tvalid_0's binary_logloss: 0.674817\n",
      "[43]\tvalid_0's l1: 0.485295\tvalid_0's binary_logloss: 0.674401\n",
      "[44]\tvalid_0's l1: 0.485186\tvalid_0's binary_logloss: 0.673987\n",
      "Early stopping, best iteration is:\n",
      "[39]\tvalid_0's l1: 0.485263\tvalid_0's binary_logloss: 0.673945\n",
      "[1]\tvalid_0's l1: 0.500631\tvalid_0's binary_logloss: 0.694891\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500818\tvalid_0's binary_logloss: 0.695295\n",
      "[3]\tvalid_0's l1: 0.500916\tvalid_0's binary_logloss: 0.695609\n",
      "[4]\tvalid_0's l1: 0.500713\tvalid_0's binary_logloss: 0.695268\n",
      "[5]\tvalid_0's l1: 0.500844\tvalid_0's binary_logloss: 0.695611\n",
      "[6]\tvalid_0's l1: 0.500546\tvalid_0's binary_logloss: 0.695204\n",
      "Early stopping, best iteration is:\n",
      "[1]\tvalid_0's l1: 0.500631\tvalid_0's binary_logloss: 0.694891\n",
      "[1]\tvalid_0's l1: 0.500616\tvalid_0's binary_logloss: 0.694936\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500514\tvalid_0's binary_logloss: 0.694931\n",
      "[3]\tvalid_0's l1: 0.499897\tvalid_0's binary_logloss: 0.694146\n",
      "[4]\tvalid_0's l1: 0.4998\tvalid_0's binary_logloss: 0.694404\n",
      "[5]\tvalid_0's l1: 0.500325\tvalid_0's binary_logloss: 0.695595\n",
      "[6]\tvalid_0's l1: 0.500239\tvalid_0's binary_logloss: 0.695985\n",
      "[7]\tvalid_0's l1: 0.500347\tvalid_0's binary_logloss: 0.696931\n",
      "[8]\tvalid_0's l1: 0.499872\tvalid_0's binary_logloss: 0.696682\n",
      "Early stopping, best iteration is:\n",
      "[3]\tvalid_0's l1: 0.499897\tvalid_0's binary_logloss: 0.694146\n",
      "[1]\tvalid_0's l1: 0.500584\tvalid_0's binary_logloss: 0.694883\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500123\tvalid_0's binary_logloss: 0.694204\n",
      "[3]\tvalid_0's l1: 0.499469\tvalid_0's binary_logloss: 0.693446\n",
      "[4]\tvalid_0's l1: 0.498243\tvalid_0's binary_logloss: 0.691748\n",
      "[5]\tvalid_0's l1: 0.497858\tvalid_0's binary_logloss: 0.691258\n",
      "[6]\tvalid_0's l1: 0.496607\tvalid_0's binary_logloss: 0.689959\n",
      "[7]\tvalid_0's l1: 0.495836\tvalid_0's binary_logloss: 0.689488\n",
      "[8]\tvalid_0's l1: 0.494407\tvalid_0's binary_logloss: 0.688408\n",
      "[9]\tvalid_0's l1: 0.493904\tvalid_0's binary_logloss: 0.68816\n",
      "[10]\tvalid_0's l1: 0.493292\tvalid_0's binary_logloss: 0.68791\n",
      "[11]\tvalid_0's l1: 0.492952\tvalid_0's binary_logloss: 0.689128\n",
      "[12]\tvalid_0's l1: 0.492689\tvalid_0's binary_logloss: 0.689758\n",
      "[13]\tvalid_0's l1: 0.492135\tvalid_0's binary_logloss: 0.69076\n",
      "[14]\tvalid_0's l1: 0.491999\tvalid_0's binary_logloss: 0.691995\n",
      "[15]\tvalid_0's l1: 0.491614\tvalid_0's binary_logloss: 0.693189\n",
      "Early stopping, best iteration is:\n",
      "[10]\tvalid_0's l1: 0.493292\tvalid_0's binary_logloss: 0.68791\n",
      "[1]\tvalid_0's l1: 0.499873\tvalid_0's binary_logloss: 0.693842\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.498368\tvalid_0's binary_logloss: 0.691546\n",
      "[3]\tvalid_0's l1: 0.496842\tvalid_0's binary_logloss: 0.68947\n",
      "[4]\tvalid_0's l1: 0.496215\tvalid_0's binary_logloss: 0.688619\n",
      "[5]\tvalid_0's l1: 0.495438\tvalid_0's binary_logloss: 0.688266\n",
      "[6]\tvalid_0's l1: 0.494569\tvalid_0's binary_logloss: 0.686886\n",
      "[7]\tvalid_0's l1: 0.494049\tvalid_0's binary_logloss: 0.686528\n",
      "[8]\tvalid_0's l1: 0.4935\tvalid_0's binary_logloss: 0.686414\n",
      "[9]\tvalid_0's l1: 0.4923\tvalid_0's binary_logloss: 0.684783\n",
      "[10]\tvalid_0's l1: 0.491505\tvalid_0's binary_logloss: 0.683958\n",
      "[11]\tvalid_0's l1: 0.490807\tvalid_0's binary_logloss: 0.683884\n",
      "[12]\tvalid_0's l1: 0.488958\tvalid_0's binary_logloss: 0.681472\n",
      "[13]\tvalid_0's l1: 0.488366\tvalid_0's binary_logloss: 0.681951\n",
      "[14]\tvalid_0's l1: 0.487311\tvalid_0's binary_logloss: 0.681311\n",
      "[15]\tvalid_0's l1: 0.486386\tvalid_0's binary_logloss: 0.680763\n",
      "[16]\tvalid_0's l1: 0.485519\tvalid_0's binary_logloss: 0.680267\n",
      "[17]\tvalid_0's l1: 0.485044\tvalid_0's binary_logloss: 0.680816\n",
      "[18]\tvalid_0's l1: 0.48421\tvalid_0's binary_logloss: 0.679634\n",
      "[19]\tvalid_0's l1: 0.48439\tvalid_0's binary_logloss: 0.681119\n",
      "[20]\tvalid_0's l1: 0.484065\tvalid_0's binary_logloss: 0.68129\n",
      "[21]\tvalid_0's l1: 0.483398\tvalid_0's binary_logloss: 0.681332\n",
      "[22]\tvalid_0's l1: 0.483354\tvalid_0's binary_logloss: 0.682364\n",
      "[23]\tvalid_0's l1: 0.483411\tvalid_0's binary_logloss: 0.684782\n",
      "Early stopping, best iteration is:\n",
      "[18]\tvalid_0's l1: 0.48421\tvalid_0's binary_logloss: 0.679634\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1]\tvalid_0's l1: 0.500425\tvalid_0's binary_logloss: 0.694526\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.499146\tvalid_0's binary_logloss: 0.692013\n",
      "[3]\tvalid_0's l1: 0.497938\tvalid_0's binary_logloss: 0.68962\n",
      "[4]\tvalid_0's l1: 0.497596\tvalid_0's binary_logloss: 0.689048\n",
      "[5]\tvalid_0's l1: 0.496723\tvalid_0's binary_logloss: 0.687576\n",
      "[6]\tvalid_0's l1: 0.496399\tvalid_0's binary_logloss: 0.687076\n",
      "[7]\tvalid_0's l1: 0.495396\tvalid_0's binary_logloss: 0.68544\n",
      "[8]\tvalid_0's l1: 0.494297\tvalid_0's binary_logloss: 0.683625\n",
      "[9]\tvalid_0's l1: 0.492936\tvalid_0's binary_logloss: 0.681283\n",
      "[10]\tvalid_0's l1: 0.492053\tvalid_0's binary_logloss: 0.680088\n",
      "[11]\tvalid_0's l1: 0.491426\tvalid_0's binary_logloss: 0.678964\n",
      "[12]\tvalid_0's l1: 0.491487\tvalid_0's binary_logloss: 0.67921\n",
      "[13]\tvalid_0's l1: 0.491273\tvalid_0's binary_logloss: 0.679008\n",
      "[14]\tvalid_0's l1: 0.490748\tvalid_0's binary_logloss: 0.678504\n",
      "[15]\tvalid_0's l1: 0.489916\tvalid_0's binary_logloss: 0.677785\n",
      "[16]\tvalid_0's l1: 0.489818\tvalid_0's binary_logloss: 0.677849\n",
      "[17]\tvalid_0's l1: 0.488978\tvalid_0's binary_logloss: 0.676451\n",
      "[18]\tvalid_0's l1: 0.488478\tvalid_0's binary_logloss: 0.676471\n",
      "[19]\tvalid_0's l1: 0.488142\tvalid_0's binary_logloss: 0.676025\n",
      "[20]\tvalid_0's l1: 0.487432\tvalid_0's binary_logloss: 0.675907\n",
      "[21]\tvalid_0's l1: 0.48683\tvalid_0's binary_logloss: 0.674612\n",
      "[22]\tvalid_0's l1: 0.486058\tvalid_0's binary_logloss: 0.673422\n",
      "[23]\tvalid_0's l1: 0.485656\tvalid_0's binary_logloss: 0.674257\n",
      "[24]\tvalid_0's l1: 0.485803\tvalid_0's binary_logloss: 0.675175\n",
      "[25]\tvalid_0's l1: 0.485389\tvalid_0's binary_logloss: 0.675015\n",
      "[26]\tvalid_0's l1: 0.485002\tvalid_0's binary_logloss: 0.675581\n",
      "[27]\tvalid_0's l1: 0.484678\tvalid_0's binary_logloss: 0.675261\n",
      "Early stopping, best iteration is:\n",
      "[22]\tvalid_0's l1: 0.486058\tvalid_0's binary_logloss: 0.673422\n",
      "[1]\tvalid_0's l1: 0.500676\tvalid_0's binary_logloss: 0.69501\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.499976\tvalid_0's binary_logloss: 0.693718\n",
      "[3]\tvalid_0's l1: 0.500038\tvalid_0's binary_logloss: 0.69391\n",
      "[4]\tvalid_0's l1: 0.500051\tvalid_0's binary_logloss: 0.694254\n",
      "[5]\tvalid_0's l1: 0.499975\tvalid_0's binary_logloss: 0.694351\n",
      "[6]\tvalid_0's l1: 0.499803\tvalid_0's binary_logloss: 0.694391\n",
      "[7]\tvalid_0's l1: 0.499577\tvalid_0's binary_logloss: 0.694341\n",
      "Early stopping, best iteration is:\n",
      "[2]\tvalid_0's l1: 0.499976\tvalid_0's binary_logloss: 0.693718\n",
      "[1]\tvalid_0's l1: 0.499841\tvalid_0's binary_logloss: 0.69327\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.498341\tvalid_0's binary_logloss: 0.690479\n",
      "[3]\tvalid_0's l1: 0.498144\tvalid_0's binary_logloss: 0.690543\n",
      "[4]\tvalid_0's l1: 0.498074\tvalid_0's binary_logloss: 0.690916\n",
      "[5]\tvalid_0's l1: 0.496927\tvalid_0's binary_logloss: 0.689454\n",
      "[6]\tvalid_0's l1: 0.497087\tvalid_0's binary_logloss: 0.690131\n",
      "[7]\tvalid_0's l1: 0.497153\tvalid_0's binary_logloss: 0.691103\n",
      "[8]\tvalid_0's l1: 0.496512\tvalid_0's binary_logloss: 0.690333\n",
      "[9]\tvalid_0's l1: 0.495506\tvalid_0's binary_logloss: 0.689246\n",
      "[10]\tvalid_0's l1: 0.49431\tvalid_0's binary_logloss: 0.687873\n",
      "[11]\tvalid_0's l1: 0.494024\tvalid_0's binary_logloss: 0.687935\n",
      "[12]\tvalid_0's l1: 0.492861\tvalid_0's binary_logloss: 0.686658\n",
      "[13]\tvalid_0's l1: 0.493037\tvalid_0's binary_logloss: 0.687808\n",
      "[14]\tvalid_0's l1: 0.493684\tvalid_0's binary_logloss: 0.690564\n",
      "[15]\tvalid_0's l1: 0.494209\tvalid_0's binary_logloss: 0.69307\n",
      "[16]\tvalid_0's l1: 0.494729\tvalid_0's binary_logloss: 0.695784\n",
      "[17]\tvalid_0's l1: 0.494532\tvalid_0's binary_logloss: 0.696528\n",
      "Early stopping, best iteration is:\n",
      "[12]\tvalid_0's l1: 0.492861\tvalid_0's binary_logloss: 0.686658\n",
      "[1]\tvalid_0's l1: 0.500584\tvalid_0's binary_logloss: 0.694883\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500123\tvalid_0's binary_logloss: 0.694204\n",
      "[3]\tvalid_0's l1: 0.499469\tvalid_0's binary_logloss: 0.693446\n",
      "[4]\tvalid_0's l1: 0.498243\tvalid_0's binary_logloss: 0.691748\n",
      "[5]\tvalid_0's l1: 0.497858\tvalid_0's binary_logloss: 0.691258\n",
      "[6]\tvalid_0's l1: 0.496607\tvalid_0's binary_logloss: 0.689959\n",
      "[7]\tvalid_0's l1: 0.495836\tvalid_0's binary_logloss: 0.689488\n",
      "[8]\tvalid_0's l1: 0.494407\tvalid_0's binary_logloss: 0.688408\n",
      "[9]\tvalid_0's l1: 0.493904\tvalid_0's binary_logloss: 0.68816\n",
      "[10]\tvalid_0's l1: 0.493292\tvalid_0's binary_logloss: 0.68791\n",
      "[11]\tvalid_0's l1: 0.492952\tvalid_0's binary_logloss: 0.689128\n",
      "[12]\tvalid_0's l1: 0.492689\tvalid_0's binary_logloss: 0.689758\n",
      "[13]\tvalid_0's l1: 0.492135\tvalid_0's binary_logloss: 0.69076\n",
      "[14]\tvalid_0's l1: 0.491999\tvalid_0's binary_logloss: 0.691995\n",
      "[15]\tvalid_0's l1: 0.491614\tvalid_0's binary_logloss: 0.693189\n",
      "Early stopping, best iteration is:\n",
      "[10]\tvalid_0's l1: 0.493292\tvalid_0's binary_logloss: 0.68791\n",
      "[1]\tvalid_0's l1: 0.499873\tvalid_0's binary_logloss: 0.693842\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.498368\tvalid_0's binary_logloss: 0.691546\n",
      "[3]\tvalid_0's l1: 0.496842\tvalid_0's binary_logloss: 0.68947\n",
      "[4]\tvalid_0's l1: 0.496215\tvalid_0's binary_logloss: 0.688619\n",
      "[5]\tvalid_0's l1: 0.495438\tvalid_0's binary_logloss: 0.688266\n",
      "[6]\tvalid_0's l1: 0.494569\tvalid_0's binary_logloss: 0.686886\n",
      "[7]\tvalid_0's l1: 0.494049\tvalid_0's binary_logloss: 0.686528\n",
      "[8]\tvalid_0's l1: 0.4935\tvalid_0's binary_logloss: 0.686414\n",
      "[9]\tvalid_0's l1: 0.4923\tvalid_0's binary_logloss: 0.684783\n",
      "[10]\tvalid_0's l1: 0.491505\tvalid_0's binary_logloss: 0.683958\n",
      "[11]\tvalid_0's l1: 0.490807\tvalid_0's binary_logloss: 0.683884\n",
      "[12]\tvalid_0's l1: 0.488958\tvalid_0's binary_logloss: 0.681472\n",
      "[13]\tvalid_0's l1: 0.488366\tvalid_0's binary_logloss: 0.681951\n",
      "[14]\tvalid_0's l1: 0.487311\tvalid_0's binary_logloss: 0.681311\n",
      "[15]\tvalid_0's l1: 0.486386\tvalid_0's binary_logloss: 0.680763\n",
      "[16]\tvalid_0's l1: 0.485519\tvalid_0's binary_logloss: 0.680267\n",
      "[17]\tvalid_0's l1: 0.485044\tvalid_0's binary_logloss: 0.680816\n",
      "[18]\tvalid_0's l1: 0.48421\tvalid_0's binary_logloss: 0.679634\n",
      "[19]\tvalid_0's l1: 0.48439\tvalid_0's binary_logloss: 0.681119\n",
      "[20]\tvalid_0's l1: 0.484065\tvalid_0's binary_logloss: 0.68129\n",
      "[21]\tvalid_0's l1: 0.483398\tvalid_0's binary_logloss: 0.681332\n",
      "[22]\tvalid_0's l1: 0.483354\tvalid_0's binary_logloss: 0.682364\n",
      "[23]\tvalid_0's l1: 0.483411\tvalid_0's binary_logloss: 0.684782\n",
      "Early stopping, best iteration is:\n",
      "[18]\tvalid_0's l1: 0.48421\tvalid_0's binary_logloss: 0.679634\n",
      "[1]\tvalid_0's l1: 0.500425\tvalid_0's binary_logloss: 0.694526\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.499146\tvalid_0's binary_logloss: 0.692013\n",
      "[3]\tvalid_0's l1: 0.497938\tvalid_0's binary_logloss: 0.68962\n",
      "[4]\tvalid_0's l1: 0.497596\tvalid_0's binary_logloss: 0.689048\n",
      "[5]\tvalid_0's l1: 0.496723\tvalid_0's binary_logloss: 0.687576\n",
      "[6]\tvalid_0's l1: 0.496399\tvalid_0's binary_logloss: 0.687076\n",
      "[7]\tvalid_0's l1: 0.495396\tvalid_0's binary_logloss: 0.68544\n",
      "[8]\tvalid_0's l1: 0.494297\tvalid_0's binary_logloss: 0.683625\n",
      "[9]\tvalid_0's l1: 0.492936\tvalid_0's binary_logloss: 0.681283\n",
      "[10]\tvalid_0's l1: 0.492053\tvalid_0's binary_logloss: 0.680088\n",
      "[11]\tvalid_0's l1: 0.491426\tvalid_0's binary_logloss: 0.678964\n",
      "[12]\tvalid_0's l1: 0.491487\tvalid_0's binary_logloss: 0.67921\n",
      "[13]\tvalid_0's l1: 0.491273\tvalid_0's binary_logloss: 0.679008\n",
      "[14]\tvalid_0's l1: 0.490748\tvalid_0's binary_logloss: 0.678504\n",
      "[15]\tvalid_0's l1: 0.489916\tvalid_0's binary_logloss: 0.677785\n",
      "[16]\tvalid_0's l1: 0.489818\tvalid_0's binary_logloss: 0.677849\n",
      "[17]\tvalid_0's l1: 0.488978\tvalid_0's binary_logloss: 0.676451\n",
      "[18]\tvalid_0's l1: 0.488478\tvalid_0's binary_logloss: 0.676471\n",
      "[19]\tvalid_0's l1: 0.488142\tvalid_0's binary_logloss: 0.676025\n",
      "[20]\tvalid_0's l1: 0.487432\tvalid_0's binary_logloss: 0.675907\n",
      "[21]\tvalid_0's l1: 0.48683\tvalid_0's binary_logloss: 0.674612\n",
      "[22]\tvalid_0's l1: 0.486058\tvalid_0's binary_logloss: 0.673422\n",
      "[23]\tvalid_0's l1: 0.485656\tvalid_0's binary_logloss: 0.674257\n",
      "[24]\tvalid_0's l1: 0.485803\tvalid_0's binary_logloss: 0.675175\n",
      "[25]\tvalid_0's l1: 0.485389\tvalid_0's binary_logloss: 0.675015\n",
      "[26]\tvalid_0's l1: 0.485002\tvalid_0's binary_logloss: 0.675581\n",
      "[27]\tvalid_0's l1: 0.484678\tvalid_0's binary_logloss: 0.675261\n",
      "Early stopping, best iteration is:\n",
      "[22]\tvalid_0's l1: 0.486058\tvalid_0's binary_logloss: 0.673422\n",
      "[1]\tvalid_0's l1: 0.500676\tvalid_0's binary_logloss: 0.69501\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.499976\tvalid_0's binary_logloss: 0.693718\n",
      "[3]\tvalid_0's l1: 0.500038\tvalid_0's binary_logloss: 0.69391\n",
      "[4]\tvalid_0's l1: 0.500051\tvalid_0's binary_logloss: 0.694254\n",
      "[5]\tvalid_0's l1: 0.499975\tvalid_0's binary_logloss: 0.694351\n",
      "[6]\tvalid_0's l1: 0.499803\tvalid_0's binary_logloss: 0.694391\n",
      "[7]\tvalid_0's l1: 0.499577\tvalid_0's binary_logloss: 0.694341\n",
      "Early stopping, best iteration is:\n",
      "[2]\tvalid_0's l1: 0.499976\tvalid_0's binary_logloss: 0.693718\n",
      "[1]\tvalid_0's l1: 0.499841\tvalid_0's binary_logloss: 0.69327\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.498341\tvalid_0's binary_logloss: 0.690479\n",
      "[3]\tvalid_0's l1: 0.498144\tvalid_0's binary_logloss: 0.690543\n",
      "[4]\tvalid_0's l1: 0.498074\tvalid_0's binary_logloss: 0.690916\n",
      "[5]\tvalid_0's l1: 0.496927\tvalid_0's binary_logloss: 0.689454\n",
      "[6]\tvalid_0's l1: 0.497087\tvalid_0's binary_logloss: 0.690131\n",
      "[7]\tvalid_0's l1: 0.497153\tvalid_0's binary_logloss: 0.691103\n",
      "[8]\tvalid_0's l1: 0.496512\tvalid_0's binary_logloss: 0.690333\n",
      "[9]\tvalid_0's l1: 0.495506\tvalid_0's binary_logloss: 0.689246\n",
      "[10]\tvalid_0's l1: 0.49431\tvalid_0's binary_logloss: 0.687873\n",
      "[11]\tvalid_0's l1: 0.494024\tvalid_0's binary_logloss: 0.687935\n",
      "[12]\tvalid_0's l1: 0.492861\tvalid_0's binary_logloss: 0.686658\n",
      "[13]\tvalid_0's l1: 0.493037\tvalid_0's binary_logloss: 0.687808\n",
      "[14]\tvalid_0's l1: 0.493684\tvalid_0's binary_logloss: 0.690564\n",
      "[15]\tvalid_0's l1: 0.494209\tvalid_0's binary_logloss: 0.69307\n",
      "[16]\tvalid_0's l1: 0.494729\tvalid_0's binary_logloss: 0.695784\n",
      "[17]\tvalid_0's l1: 0.494532\tvalid_0's binary_logloss: 0.696528\n",
      "Early stopping, best iteration is:\n",
      "[12]\tvalid_0's l1: 0.492861\tvalid_0's binary_logloss: 0.686658\n",
      "[1]\tvalid_0's l1: 0.500584\tvalid_0's binary_logloss: 0.694883\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500123\tvalid_0's binary_logloss: 0.694204\n",
      "[3]\tvalid_0's l1: 0.499469\tvalid_0's binary_logloss: 0.693446\n",
      "[4]\tvalid_0's l1: 0.498243\tvalid_0's binary_logloss: 0.691748\n",
      "[5]\tvalid_0's l1: 0.497858\tvalid_0's binary_logloss: 0.691258\n",
      "[6]\tvalid_0's l1: 0.496607\tvalid_0's binary_logloss: 0.689959\n",
      "[7]\tvalid_0's l1: 0.495836\tvalid_0's binary_logloss: 0.689488\n",
      "[8]\tvalid_0's l1: 0.494407\tvalid_0's binary_logloss: 0.688408\n",
      "[9]\tvalid_0's l1: 0.493904\tvalid_0's binary_logloss: 0.68816\n",
      "[10]\tvalid_0's l1: 0.493292\tvalid_0's binary_logloss: 0.68791\n",
      "[11]\tvalid_0's l1: 0.492952\tvalid_0's binary_logloss: 0.689128\n",
      "[12]\tvalid_0's l1: 0.492689\tvalid_0's binary_logloss: 0.689758\n",
      "[13]\tvalid_0's l1: 0.492135\tvalid_0's binary_logloss: 0.69076\n",
      "[14]\tvalid_0's l1: 0.491999\tvalid_0's binary_logloss: 0.691995\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[15]\tvalid_0's l1: 0.491614\tvalid_0's binary_logloss: 0.693189\n",
      "Early stopping, best iteration is:\n",
      "[10]\tvalid_0's l1: 0.493292\tvalid_0's binary_logloss: 0.68791\n",
      "[1]\tvalid_0's l1: 0.499873\tvalid_0's binary_logloss: 0.693842\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.498368\tvalid_0's binary_logloss: 0.691546\n",
      "[3]\tvalid_0's l1: 0.496842\tvalid_0's binary_logloss: 0.68947\n",
      "[4]\tvalid_0's l1: 0.496215\tvalid_0's binary_logloss: 0.688619\n",
      "[5]\tvalid_0's l1: 0.495438\tvalid_0's binary_logloss: 0.688266\n",
      "[6]\tvalid_0's l1: 0.494569\tvalid_0's binary_logloss: 0.686886\n",
      "[7]\tvalid_0's l1: 0.494049\tvalid_0's binary_logloss: 0.686528\n",
      "[8]\tvalid_0's l1: 0.4935\tvalid_0's binary_logloss: 0.686414\n",
      "[9]\tvalid_0's l1: 0.4923\tvalid_0's binary_logloss: 0.684783\n",
      "[10]\tvalid_0's l1: 0.491505\tvalid_0's binary_logloss: 0.683958\n",
      "[11]\tvalid_0's l1: 0.490807\tvalid_0's binary_logloss: 0.683884\n",
      "[12]\tvalid_0's l1: 0.488958\tvalid_0's binary_logloss: 0.681472\n",
      "[13]\tvalid_0's l1: 0.488366\tvalid_0's binary_logloss: 0.681951\n",
      "[14]\tvalid_0's l1: 0.487311\tvalid_0's binary_logloss: 0.681311\n",
      "[15]\tvalid_0's l1: 0.486386\tvalid_0's binary_logloss: 0.680763\n",
      "[16]\tvalid_0's l1: 0.485519\tvalid_0's binary_logloss: 0.680267\n",
      "[17]\tvalid_0's l1: 0.485044\tvalid_0's binary_logloss: 0.680816\n",
      "[18]\tvalid_0's l1: 0.48421\tvalid_0's binary_logloss: 0.679634\n",
      "[19]\tvalid_0's l1: 0.48439\tvalid_0's binary_logloss: 0.681119\n",
      "[20]\tvalid_0's l1: 0.484065\tvalid_0's binary_logloss: 0.68129\n",
      "[21]\tvalid_0's l1: 0.483398\tvalid_0's binary_logloss: 0.681332\n",
      "[22]\tvalid_0's l1: 0.483354\tvalid_0's binary_logloss: 0.682364\n",
      "[23]\tvalid_0's l1: 0.483411\tvalid_0's binary_logloss: 0.684782\n",
      "Early stopping, best iteration is:\n",
      "[18]\tvalid_0's l1: 0.48421\tvalid_0's binary_logloss: 0.679634\n",
      "[1]\tvalid_0's l1: 0.500425\tvalid_0's binary_logloss: 0.694526\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.499146\tvalid_0's binary_logloss: 0.692013\n",
      "[3]\tvalid_0's l1: 0.497938\tvalid_0's binary_logloss: 0.68962\n",
      "[4]\tvalid_0's l1: 0.497596\tvalid_0's binary_logloss: 0.689048\n",
      "[5]\tvalid_0's l1: 0.496723\tvalid_0's binary_logloss: 0.687576\n",
      "[6]\tvalid_0's l1: 0.496399\tvalid_0's binary_logloss: 0.687076\n",
      "[7]\tvalid_0's l1: 0.495396\tvalid_0's binary_logloss: 0.68544\n",
      "[8]\tvalid_0's l1: 0.494297\tvalid_0's binary_logloss: 0.683625\n",
      "[9]\tvalid_0's l1: 0.492936\tvalid_0's binary_logloss: 0.681283\n",
      "[10]\tvalid_0's l1: 0.492053\tvalid_0's binary_logloss: 0.680088\n",
      "[11]\tvalid_0's l1: 0.491426\tvalid_0's binary_logloss: 0.678964\n",
      "[12]\tvalid_0's l1: 0.491487\tvalid_0's binary_logloss: 0.67921\n",
      "[13]\tvalid_0's l1: 0.491273\tvalid_0's binary_logloss: 0.679008\n",
      "[14]\tvalid_0's l1: 0.490748\tvalid_0's binary_logloss: 0.678504\n",
      "[15]\tvalid_0's l1: 0.489916\tvalid_0's binary_logloss: 0.677785\n",
      "[16]\tvalid_0's l1: 0.489818\tvalid_0's binary_logloss: 0.677849\n",
      "[17]\tvalid_0's l1: 0.488978\tvalid_0's binary_logloss: 0.676451\n",
      "[18]\tvalid_0's l1: 0.488478\tvalid_0's binary_logloss: 0.676471\n",
      "[19]\tvalid_0's l1: 0.488142\tvalid_0's binary_logloss: 0.676025\n",
      "[20]\tvalid_0's l1: 0.487432\tvalid_0's binary_logloss: 0.675907\n",
      "[21]\tvalid_0's l1: 0.48683\tvalid_0's binary_logloss: 0.674612\n",
      "[22]\tvalid_0's l1: 0.486058\tvalid_0's binary_logloss: 0.673422\n",
      "[23]\tvalid_0's l1: 0.485656\tvalid_0's binary_logloss: 0.674257\n",
      "[24]\tvalid_0's l1: 0.485803\tvalid_0's binary_logloss: 0.675175\n",
      "[25]\tvalid_0's l1: 0.485389\tvalid_0's binary_logloss: 0.675015\n",
      "[26]\tvalid_0's l1: 0.485002\tvalid_0's binary_logloss: 0.675581\n",
      "[27]\tvalid_0's l1: 0.484678\tvalid_0's binary_logloss: 0.675261\n",
      "Early stopping, best iteration is:\n",
      "[22]\tvalid_0's l1: 0.486058\tvalid_0's binary_logloss: 0.673422\n",
      "[1]\tvalid_0's l1: 0.500676\tvalid_0's binary_logloss: 0.69501\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.499976\tvalid_0's binary_logloss: 0.693718\n",
      "[3]\tvalid_0's l1: 0.500038\tvalid_0's binary_logloss: 0.69391\n",
      "[4]\tvalid_0's l1: 0.500051\tvalid_0's binary_logloss: 0.694254\n",
      "[5]\tvalid_0's l1: 0.499975\tvalid_0's binary_logloss: 0.694351\n",
      "[6]\tvalid_0's l1: 0.499803\tvalid_0's binary_logloss: 0.694391\n",
      "[7]\tvalid_0's l1: 0.499577\tvalid_0's binary_logloss: 0.694341\n",
      "Early stopping, best iteration is:\n",
      "[2]\tvalid_0's l1: 0.499976\tvalid_0's binary_logloss: 0.693718\n",
      "[1]\tvalid_0's l1: 0.499841\tvalid_0's binary_logloss: 0.69327\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.498341\tvalid_0's binary_logloss: 0.690479\n",
      "[3]\tvalid_0's l1: 0.498144\tvalid_0's binary_logloss: 0.690543\n",
      "[4]\tvalid_0's l1: 0.498074\tvalid_0's binary_logloss: 0.690916\n",
      "[5]\tvalid_0's l1: 0.496927\tvalid_0's binary_logloss: 0.689454\n",
      "[6]\tvalid_0's l1: 0.497087\tvalid_0's binary_logloss: 0.690131\n",
      "[7]\tvalid_0's l1: 0.497153\tvalid_0's binary_logloss: 0.691103\n",
      "[8]\tvalid_0's l1: 0.496512\tvalid_0's binary_logloss: 0.690333\n",
      "[9]\tvalid_0's l1: 0.495506\tvalid_0's binary_logloss: 0.689246\n",
      "[10]\tvalid_0's l1: 0.49431\tvalid_0's binary_logloss: 0.687873\n",
      "[11]\tvalid_0's l1: 0.494024\tvalid_0's binary_logloss: 0.687935\n",
      "[12]\tvalid_0's l1: 0.492861\tvalid_0's binary_logloss: 0.686658\n",
      "[13]\tvalid_0's l1: 0.493037\tvalid_0's binary_logloss: 0.687808\n",
      "[14]\tvalid_0's l1: 0.493684\tvalid_0's binary_logloss: 0.690564\n",
      "[15]\tvalid_0's l1: 0.494209\tvalid_0's binary_logloss: 0.69307\n",
      "[16]\tvalid_0's l1: 0.494729\tvalid_0's binary_logloss: 0.695784\n",
      "[17]\tvalid_0's l1: 0.494532\tvalid_0's binary_logloss: 0.696528\n",
      "Early stopping, best iteration is:\n",
      "[12]\tvalid_0's l1: 0.492861\tvalid_0's binary_logloss: 0.686658\n",
      "[1]\tvalid_0's l1: 0.500584\tvalid_0's binary_logloss: 0.694883\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500123\tvalid_0's binary_logloss: 0.694204\n",
      "[3]\tvalid_0's l1: 0.499469\tvalid_0's binary_logloss: 0.693446\n",
      "[4]\tvalid_0's l1: 0.498243\tvalid_0's binary_logloss: 0.691748\n",
      "[5]\tvalid_0's l1: 0.497858\tvalid_0's binary_logloss: 0.691258\n",
      "[6]\tvalid_0's l1: 0.496607\tvalid_0's binary_logloss: 0.689959\n",
      "[7]\tvalid_0's l1: 0.495836\tvalid_0's binary_logloss: 0.689488\n",
      "[8]\tvalid_0's l1: 0.494407\tvalid_0's binary_logloss: 0.688408\n",
      "[9]\tvalid_0's l1: 0.493904\tvalid_0's binary_logloss: 0.68816\n",
      "[10]\tvalid_0's l1: 0.493292\tvalid_0's binary_logloss: 0.68791\n",
      "[11]\tvalid_0's l1: 0.492952\tvalid_0's binary_logloss: 0.689128\n",
      "[12]\tvalid_0's l1: 0.492689\tvalid_0's binary_logloss: 0.689758\n",
      "[13]\tvalid_0's l1: 0.492135\tvalid_0's binary_logloss: 0.69076\n",
      "[14]\tvalid_0's l1: 0.491999\tvalid_0's binary_logloss: 0.691995\n",
      "[15]\tvalid_0's l1: 0.491614\tvalid_0's binary_logloss: 0.693189\n",
      "Early stopping, best iteration is:\n",
      "[10]\tvalid_0's l1: 0.493292\tvalid_0's binary_logloss: 0.68791\n",
      "[1]\tvalid_0's l1: 0.499873\tvalid_0's binary_logloss: 0.693842\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.498368\tvalid_0's binary_logloss: 0.691546\n",
      "[3]\tvalid_0's l1: 0.496842\tvalid_0's binary_logloss: 0.68947\n",
      "[4]\tvalid_0's l1: 0.496215\tvalid_0's binary_logloss: 0.688619\n",
      "[5]\tvalid_0's l1: 0.495438\tvalid_0's binary_logloss: 0.688266\n",
      "[6]\tvalid_0's l1: 0.494569\tvalid_0's binary_logloss: 0.686886\n",
      "[7]\tvalid_0's l1: 0.494049\tvalid_0's binary_logloss: 0.686528\n",
      "[8]\tvalid_0's l1: 0.4935\tvalid_0's binary_logloss: 0.686414\n",
      "[9]\tvalid_0's l1: 0.4923\tvalid_0's binary_logloss: 0.684783\n",
      "[10]\tvalid_0's l1: 0.491505\tvalid_0's binary_logloss: 0.683958\n",
      "[11]\tvalid_0's l1: 0.490807\tvalid_0's binary_logloss: 0.683884\n",
      "[12]\tvalid_0's l1: 0.488958\tvalid_0's binary_logloss: 0.681472\n",
      "[13]\tvalid_0's l1: 0.488366\tvalid_0's binary_logloss: 0.681951\n",
      "[14]\tvalid_0's l1: 0.487311\tvalid_0's binary_logloss: 0.681311\n",
      "[15]\tvalid_0's l1: 0.486386\tvalid_0's binary_logloss: 0.680763\n",
      "[16]\tvalid_0's l1: 0.485519\tvalid_0's binary_logloss: 0.680267\n",
      "[17]\tvalid_0's l1: 0.485044\tvalid_0's binary_logloss: 0.680816\n",
      "[18]\tvalid_0's l1: 0.48421\tvalid_0's binary_logloss: 0.679634\n",
      "[19]\tvalid_0's l1: 0.48439\tvalid_0's binary_logloss: 0.681119\n",
      "[20]\tvalid_0's l1: 0.484065\tvalid_0's binary_logloss: 0.68129\n",
      "[21]\tvalid_0's l1: 0.483398\tvalid_0's binary_logloss: 0.681332\n",
      "[22]\tvalid_0's l1: 0.483354\tvalid_0's binary_logloss: 0.682364\n",
      "[23]\tvalid_0's l1: 0.483411\tvalid_0's binary_logloss: 0.684782\n",
      "Early stopping, best iteration is:\n",
      "[18]\tvalid_0's l1: 0.48421\tvalid_0's binary_logloss: 0.679634\n",
      "[1]\tvalid_0's l1: 0.500425\tvalid_0's binary_logloss: 0.694526\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.499146\tvalid_0's binary_logloss: 0.692013\n",
      "[3]\tvalid_0's l1: 0.497938\tvalid_0's binary_logloss: 0.68962\n",
      "[4]\tvalid_0's l1: 0.497596\tvalid_0's binary_logloss: 0.689048\n",
      "[5]\tvalid_0's l1: 0.496723\tvalid_0's binary_logloss: 0.687576\n",
      "[6]\tvalid_0's l1: 0.496399\tvalid_0's binary_logloss: 0.687076\n",
      "[7]\tvalid_0's l1: 0.495396\tvalid_0's binary_logloss: 0.68544\n",
      "[8]\tvalid_0's l1: 0.494297\tvalid_0's binary_logloss: 0.683625\n",
      "[9]\tvalid_0's l1: 0.492936\tvalid_0's binary_logloss: 0.681283\n",
      "[10]\tvalid_0's l1: 0.492053\tvalid_0's binary_logloss: 0.680088\n",
      "[11]\tvalid_0's l1: 0.491426\tvalid_0's binary_logloss: 0.678964\n",
      "[12]\tvalid_0's l1: 0.491487\tvalid_0's binary_logloss: 0.67921\n",
      "[13]\tvalid_0's l1: 0.491273\tvalid_0's binary_logloss: 0.679008\n",
      "[14]\tvalid_0's l1: 0.490748\tvalid_0's binary_logloss: 0.678504\n",
      "[15]\tvalid_0's l1: 0.489916\tvalid_0's binary_logloss: 0.677785\n",
      "[16]\tvalid_0's l1: 0.489818\tvalid_0's binary_logloss: 0.677849\n",
      "[17]\tvalid_0's l1: 0.488978\tvalid_0's binary_logloss: 0.676451\n",
      "[18]\tvalid_0's l1: 0.488478\tvalid_0's binary_logloss: 0.676471\n",
      "[19]\tvalid_0's l1: 0.488142\tvalid_0's binary_logloss: 0.676025\n",
      "[20]\tvalid_0's l1: 0.487432\tvalid_0's binary_logloss: 0.675907\n",
      "[21]\tvalid_0's l1: 0.48683\tvalid_0's binary_logloss: 0.674612\n",
      "[22]\tvalid_0's l1: 0.486058\tvalid_0's binary_logloss: 0.673422\n",
      "[23]\tvalid_0's l1: 0.485656\tvalid_0's binary_logloss: 0.674257\n",
      "[24]\tvalid_0's l1: 0.485803\tvalid_0's binary_logloss: 0.675175\n",
      "[25]\tvalid_0's l1: 0.485389\tvalid_0's binary_logloss: 0.675015\n",
      "[26]\tvalid_0's l1: 0.485002\tvalid_0's binary_logloss: 0.675581\n",
      "[27]\tvalid_0's l1: 0.484678\tvalid_0's binary_logloss: 0.675261\n",
      "Early stopping, best iteration is:\n",
      "[22]\tvalid_0's l1: 0.486058\tvalid_0's binary_logloss: 0.673422\n",
      "[1]\tvalid_0's l1: 0.500676\tvalid_0's binary_logloss: 0.69501\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.499976\tvalid_0's binary_logloss: 0.693718\n",
      "[3]\tvalid_0's l1: 0.500038\tvalid_0's binary_logloss: 0.69391\n",
      "[4]\tvalid_0's l1: 0.500051\tvalid_0's binary_logloss: 0.694254\n",
      "[5]\tvalid_0's l1: 0.499975\tvalid_0's binary_logloss: 0.694351\n",
      "[6]\tvalid_0's l1: 0.499803\tvalid_0's binary_logloss: 0.694391\n",
      "[7]\tvalid_0's l1: 0.499577\tvalid_0's binary_logloss: 0.694341\n",
      "Early stopping, best iteration is:\n",
      "[2]\tvalid_0's l1: 0.499976\tvalid_0's binary_logloss: 0.693718\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1]\tvalid_0's l1: 0.499841\tvalid_0's binary_logloss: 0.69327\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.498341\tvalid_0's binary_logloss: 0.690479\n",
      "[3]\tvalid_0's l1: 0.498144\tvalid_0's binary_logloss: 0.690543\n",
      "[4]\tvalid_0's l1: 0.498074\tvalid_0's binary_logloss: 0.690916\n",
      "[5]\tvalid_0's l1: 0.496927\tvalid_0's binary_logloss: 0.689454\n",
      "[6]\tvalid_0's l1: 0.497087\tvalid_0's binary_logloss: 0.690131\n",
      "[7]\tvalid_0's l1: 0.497153\tvalid_0's binary_logloss: 0.691103\n",
      "[8]\tvalid_0's l1: 0.496512\tvalid_0's binary_logloss: 0.690333\n",
      "[9]\tvalid_0's l1: 0.495506\tvalid_0's binary_logloss: 0.689246\n",
      "[10]\tvalid_0's l1: 0.49431\tvalid_0's binary_logloss: 0.687873\n",
      "[11]\tvalid_0's l1: 0.494024\tvalid_0's binary_logloss: 0.687935\n",
      "[12]\tvalid_0's l1: 0.492861\tvalid_0's binary_logloss: 0.686658\n",
      "[13]\tvalid_0's l1: 0.493037\tvalid_0's binary_logloss: 0.687808\n",
      "[14]\tvalid_0's l1: 0.493684\tvalid_0's binary_logloss: 0.690564\n",
      "[15]\tvalid_0's l1: 0.494209\tvalid_0's binary_logloss: 0.69307\n",
      "[16]\tvalid_0's l1: 0.494729\tvalid_0's binary_logloss: 0.695784\n",
      "[17]\tvalid_0's l1: 0.494532\tvalid_0's binary_logloss: 0.696528\n",
      "Early stopping, best iteration is:\n",
      "[12]\tvalid_0's l1: 0.492861\tvalid_0's binary_logloss: 0.686658\n",
      "[1]\tvalid_0's l1: 0.500584\tvalid_0's binary_logloss: 0.694883\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500123\tvalid_0's binary_logloss: 0.694204\n",
      "[3]\tvalid_0's l1: 0.499469\tvalid_0's binary_logloss: 0.693446\n",
      "[4]\tvalid_0's l1: 0.498243\tvalid_0's binary_logloss: 0.691748\n",
      "[5]\tvalid_0's l1: 0.497858\tvalid_0's binary_logloss: 0.691258\n",
      "[6]\tvalid_0's l1: 0.496607\tvalid_0's binary_logloss: 0.689959\n",
      "[7]\tvalid_0's l1: 0.495836\tvalid_0's binary_logloss: 0.689488\n",
      "[8]\tvalid_0's l1: 0.494407\tvalid_0's binary_logloss: 0.688408\n",
      "[9]\tvalid_0's l1: 0.493904\tvalid_0's binary_logloss: 0.68816\n",
      "[10]\tvalid_0's l1: 0.493292\tvalid_0's binary_logloss: 0.68791\n",
      "[11]\tvalid_0's l1: 0.492952\tvalid_0's binary_logloss: 0.689128\n",
      "[12]\tvalid_0's l1: 0.492689\tvalid_0's binary_logloss: 0.689758\n",
      "[13]\tvalid_0's l1: 0.492135\tvalid_0's binary_logloss: 0.69076\n",
      "[14]\tvalid_0's l1: 0.491999\tvalid_0's binary_logloss: 0.691995\n",
      "[15]\tvalid_0's l1: 0.491614\tvalid_0's binary_logloss: 0.693189\n",
      "Early stopping, best iteration is:\n",
      "[10]\tvalid_0's l1: 0.493292\tvalid_0's binary_logloss: 0.68791\n",
      "[1]\tvalid_0's l1: 0.499873\tvalid_0's binary_logloss: 0.693842\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.498368\tvalid_0's binary_logloss: 0.691546\n",
      "[3]\tvalid_0's l1: 0.496842\tvalid_0's binary_logloss: 0.68947\n",
      "[4]\tvalid_0's l1: 0.496215\tvalid_0's binary_logloss: 0.688619\n",
      "[5]\tvalid_0's l1: 0.495438\tvalid_0's binary_logloss: 0.688266\n",
      "[6]\tvalid_0's l1: 0.494569\tvalid_0's binary_logloss: 0.686886\n",
      "[7]\tvalid_0's l1: 0.494049\tvalid_0's binary_logloss: 0.686528\n",
      "[8]\tvalid_0's l1: 0.4935\tvalid_0's binary_logloss: 0.686414\n",
      "[9]\tvalid_0's l1: 0.4923\tvalid_0's binary_logloss: 0.684783\n",
      "[10]\tvalid_0's l1: 0.491505\tvalid_0's binary_logloss: 0.683958\n",
      "[11]\tvalid_0's l1: 0.490807\tvalid_0's binary_logloss: 0.683884\n",
      "[12]\tvalid_0's l1: 0.488958\tvalid_0's binary_logloss: 0.681472\n",
      "[13]\tvalid_0's l1: 0.488366\tvalid_0's binary_logloss: 0.681951\n",
      "[14]\tvalid_0's l1: 0.487311\tvalid_0's binary_logloss: 0.681311\n",
      "[15]\tvalid_0's l1: 0.486386\tvalid_0's binary_logloss: 0.680763\n",
      "[16]\tvalid_0's l1: 0.485519\tvalid_0's binary_logloss: 0.680267\n",
      "[17]\tvalid_0's l1: 0.485044\tvalid_0's binary_logloss: 0.680816\n",
      "[18]\tvalid_0's l1: 0.48421\tvalid_0's binary_logloss: 0.679634\n",
      "[19]\tvalid_0's l1: 0.48439\tvalid_0's binary_logloss: 0.681119\n",
      "[20]\tvalid_0's l1: 0.484065\tvalid_0's binary_logloss: 0.68129\n",
      "[21]\tvalid_0's l1: 0.483398\tvalid_0's binary_logloss: 0.681332\n",
      "[22]\tvalid_0's l1: 0.483354\tvalid_0's binary_logloss: 0.682364\n",
      "[23]\tvalid_0's l1: 0.483411\tvalid_0's binary_logloss: 0.684782\n",
      "Early stopping, best iteration is:\n",
      "[18]\tvalid_0's l1: 0.48421\tvalid_0's binary_logloss: 0.679634\n",
      "[1]\tvalid_0's l1: 0.500425\tvalid_0's binary_logloss: 0.694526\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.499146\tvalid_0's binary_logloss: 0.692013\n",
      "[3]\tvalid_0's l1: 0.497938\tvalid_0's binary_logloss: 0.68962\n",
      "[4]\tvalid_0's l1: 0.497596\tvalid_0's binary_logloss: 0.689048\n",
      "[5]\tvalid_0's l1: 0.496723\tvalid_0's binary_logloss: 0.687576\n",
      "[6]\tvalid_0's l1: 0.496399\tvalid_0's binary_logloss: 0.687076\n",
      "[7]\tvalid_0's l1: 0.495396\tvalid_0's binary_logloss: 0.68544\n",
      "[8]\tvalid_0's l1: 0.494297\tvalid_0's binary_logloss: 0.683625\n",
      "[9]\tvalid_0's l1: 0.492936\tvalid_0's binary_logloss: 0.681283\n",
      "[10]\tvalid_0's l1: 0.492053\tvalid_0's binary_logloss: 0.680088\n",
      "[11]\tvalid_0's l1: 0.491426\tvalid_0's binary_logloss: 0.678964\n",
      "[12]\tvalid_0's l1: 0.491487\tvalid_0's binary_logloss: 0.67921\n",
      "[13]\tvalid_0's l1: 0.491273\tvalid_0's binary_logloss: 0.679008\n",
      "[14]\tvalid_0's l1: 0.490748\tvalid_0's binary_logloss: 0.678504\n",
      "[15]\tvalid_0's l1: 0.489916\tvalid_0's binary_logloss: 0.677785\n",
      "[16]\tvalid_0's l1: 0.489818\tvalid_0's binary_logloss: 0.677849\n",
      "[17]\tvalid_0's l1: 0.488978\tvalid_0's binary_logloss: 0.676451\n",
      "[18]\tvalid_0's l1: 0.488478\tvalid_0's binary_logloss: 0.676471\n",
      "[19]\tvalid_0's l1: 0.488142\tvalid_0's binary_logloss: 0.676025\n",
      "[20]\tvalid_0's l1: 0.487432\tvalid_0's binary_logloss: 0.675907\n",
      "[21]\tvalid_0's l1: 0.48683\tvalid_0's binary_logloss: 0.674612\n",
      "[22]\tvalid_0's l1: 0.486058\tvalid_0's binary_logloss: 0.673422\n",
      "[23]\tvalid_0's l1: 0.485656\tvalid_0's binary_logloss: 0.674257\n",
      "[24]\tvalid_0's l1: 0.485803\tvalid_0's binary_logloss: 0.675175\n",
      "[25]\tvalid_0's l1: 0.485389\tvalid_0's binary_logloss: 0.675015\n",
      "[26]\tvalid_0's l1: 0.485002\tvalid_0's binary_logloss: 0.675581\n",
      "[27]\tvalid_0's l1: 0.484678\tvalid_0's binary_logloss: 0.675261\n",
      "Early stopping, best iteration is:\n",
      "[22]\tvalid_0's l1: 0.486058\tvalid_0's binary_logloss: 0.673422\n",
      "[1]\tvalid_0's l1: 0.500676\tvalid_0's binary_logloss: 0.69501\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.499976\tvalid_0's binary_logloss: 0.693718\n",
      "[3]\tvalid_0's l1: 0.500038\tvalid_0's binary_logloss: 0.69391\n",
      "[4]\tvalid_0's l1: 0.500051\tvalid_0's binary_logloss: 0.694254\n",
      "[5]\tvalid_0's l1: 0.499975\tvalid_0's binary_logloss: 0.694351\n",
      "[6]\tvalid_0's l1: 0.499803\tvalid_0's binary_logloss: 0.694391\n",
      "[7]\tvalid_0's l1: 0.499577\tvalid_0's binary_logloss: 0.694341\n",
      "Early stopping, best iteration is:\n",
      "[2]\tvalid_0's l1: 0.499976\tvalid_0's binary_logloss: 0.693718\n",
      "[1]\tvalid_0's l1: 0.499841\tvalid_0's binary_logloss: 0.69327\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.498341\tvalid_0's binary_logloss: 0.690479\n",
      "[3]\tvalid_0's l1: 0.498144\tvalid_0's binary_logloss: 0.690543\n",
      "[4]\tvalid_0's l1: 0.498074\tvalid_0's binary_logloss: 0.690916\n",
      "[5]\tvalid_0's l1: 0.496927\tvalid_0's binary_logloss: 0.689454\n",
      "[6]\tvalid_0's l1: 0.497087\tvalid_0's binary_logloss: 0.690131\n",
      "[7]\tvalid_0's l1: 0.497153\tvalid_0's binary_logloss: 0.691103\n",
      "[8]\tvalid_0's l1: 0.496512\tvalid_0's binary_logloss: 0.690333\n",
      "[9]\tvalid_0's l1: 0.495506\tvalid_0's binary_logloss: 0.689246\n",
      "[10]\tvalid_0's l1: 0.49431\tvalid_0's binary_logloss: 0.687873\n",
      "[11]\tvalid_0's l1: 0.494024\tvalid_0's binary_logloss: 0.687935\n",
      "[12]\tvalid_0's l1: 0.492861\tvalid_0's binary_logloss: 0.686658\n",
      "[13]\tvalid_0's l1: 0.493037\tvalid_0's binary_logloss: 0.687808\n",
      "[14]\tvalid_0's l1: 0.493684\tvalid_0's binary_logloss: 0.690564\n",
      "[15]\tvalid_0's l1: 0.494209\tvalid_0's binary_logloss: 0.69307\n",
      "[16]\tvalid_0's l1: 0.494729\tvalid_0's binary_logloss: 0.695784\n",
      "[17]\tvalid_0's l1: 0.494532\tvalid_0's binary_logloss: 0.696528\n",
      "Early stopping, best iteration is:\n",
      "[12]\tvalid_0's l1: 0.492861\tvalid_0's binary_logloss: 0.686658\n",
      "[1]\tvalid_0's l1: 0.500584\tvalid_0's binary_logloss: 0.694883\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500123\tvalid_0's binary_logloss: 0.694204\n",
      "[3]\tvalid_0's l1: 0.499469\tvalid_0's binary_logloss: 0.693446\n",
      "[4]\tvalid_0's l1: 0.498243\tvalid_0's binary_logloss: 0.691748\n",
      "[5]\tvalid_0's l1: 0.497858\tvalid_0's binary_logloss: 0.691258\n",
      "[6]\tvalid_0's l1: 0.496607\tvalid_0's binary_logloss: 0.689959\n",
      "[7]\tvalid_0's l1: 0.495836\tvalid_0's binary_logloss: 0.689488\n",
      "[8]\tvalid_0's l1: 0.494407\tvalid_0's binary_logloss: 0.688408\n",
      "[9]\tvalid_0's l1: 0.493904\tvalid_0's binary_logloss: 0.68816\n",
      "[10]\tvalid_0's l1: 0.493292\tvalid_0's binary_logloss: 0.68791\n",
      "[11]\tvalid_0's l1: 0.492952\tvalid_0's binary_logloss: 0.689128\n",
      "[12]\tvalid_0's l1: 0.492689\tvalid_0's binary_logloss: 0.689758\n",
      "[13]\tvalid_0's l1: 0.492135\tvalid_0's binary_logloss: 0.69076\n",
      "[14]\tvalid_0's l1: 0.491999\tvalid_0's binary_logloss: 0.691995\n",
      "[15]\tvalid_0's l1: 0.491614\tvalid_0's binary_logloss: 0.693189\n",
      "Early stopping, best iteration is:\n",
      "[10]\tvalid_0's l1: 0.493292\tvalid_0's binary_logloss: 0.68791\n",
      "[1]\tvalid_0's l1: 0.499873\tvalid_0's binary_logloss: 0.693842\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.498368\tvalid_0's binary_logloss: 0.691546\n",
      "[3]\tvalid_0's l1: 0.496842\tvalid_0's binary_logloss: 0.68947\n",
      "[4]\tvalid_0's l1: 0.496215\tvalid_0's binary_logloss: 0.688619\n",
      "[5]\tvalid_0's l1: 0.495438\tvalid_0's binary_logloss: 0.688266\n",
      "[6]\tvalid_0's l1: 0.494569\tvalid_0's binary_logloss: 0.686886\n",
      "[7]\tvalid_0's l1: 0.494049\tvalid_0's binary_logloss: 0.686528\n",
      "[8]\tvalid_0's l1: 0.4935\tvalid_0's binary_logloss: 0.686414\n",
      "[9]\tvalid_0's l1: 0.4923\tvalid_0's binary_logloss: 0.684783\n",
      "[10]\tvalid_0's l1: 0.491505\tvalid_0's binary_logloss: 0.683958\n",
      "[11]\tvalid_0's l1: 0.490807\tvalid_0's binary_logloss: 0.683884\n",
      "[12]\tvalid_0's l1: 0.488958\tvalid_0's binary_logloss: 0.681472\n",
      "[13]\tvalid_0's l1: 0.488366\tvalid_0's binary_logloss: 0.681951\n",
      "[14]\tvalid_0's l1: 0.487311\tvalid_0's binary_logloss: 0.681311\n",
      "[15]\tvalid_0's l1: 0.486386\tvalid_0's binary_logloss: 0.680763\n",
      "[16]\tvalid_0's l1: 0.485519\tvalid_0's binary_logloss: 0.680267\n",
      "[17]\tvalid_0's l1: 0.485044\tvalid_0's binary_logloss: 0.680816\n",
      "[18]\tvalid_0's l1: 0.48421\tvalid_0's binary_logloss: 0.679634\n",
      "[19]\tvalid_0's l1: 0.48439\tvalid_0's binary_logloss: 0.681119\n",
      "[20]\tvalid_0's l1: 0.484065\tvalid_0's binary_logloss: 0.68129\n",
      "[21]\tvalid_0's l1: 0.483398\tvalid_0's binary_logloss: 0.681332\n",
      "[22]\tvalid_0's l1: 0.483354\tvalid_0's binary_logloss: 0.682364\n",
      "[23]\tvalid_0's l1: 0.483411\tvalid_0's binary_logloss: 0.684782\n",
      "Early stopping, best iteration is:\n",
      "[18]\tvalid_0's l1: 0.48421\tvalid_0's binary_logloss: 0.679634\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1]\tvalid_0's l1: 0.500425\tvalid_0's binary_logloss: 0.694526\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.499146\tvalid_0's binary_logloss: 0.692013\n",
      "[3]\tvalid_0's l1: 0.497938\tvalid_0's binary_logloss: 0.68962\n",
      "[4]\tvalid_0's l1: 0.497596\tvalid_0's binary_logloss: 0.689048\n",
      "[5]\tvalid_0's l1: 0.496723\tvalid_0's binary_logloss: 0.687576\n",
      "[6]\tvalid_0's l1: 0.496399\tvalid_0's binary_logloss: 0.687076\n",
      "[7]\tvalid_0's l1: 0.495396\tvalid_0's binary_logloss: 0.68544\n",
      "[8]\tvalid_0's l1: 0.494297\tvalid_0's binary_logloss: 0.683625\n",
      "[9]\tvalid_0's l1: 0.492936\tvalid_0's binary_logloss: 0.681283\n",
      "[10]\tvalid_0's l1: 0.492053\tvalid_0's binary_logloss: 0.680088\n",
      "[11]\tvalid_0's l1: 0.491426\tvalid_0's binary_logloss: 0.678964\n",
      "[12]\tvalid_0's l1: 0.491487\tvalid_0's binary_logloss: 0.67921\n",
      "[13]\tvalid_0's l1: 0.491273\tvalid_0's binary_logloss: 0.679008\n",
      "[14]\tvalid_0's l1: 0.490748\tvalid_0's binary_logloss: 0.678504\n",
      "[15]\tvalid_0's l1: 0.489916\tvalid_0's binary_logloss: 0.677785\n",
      "[16]\tvalid_0's l1: 0.489818\tvalid_0's binary_logloss: 0.677849\n",
      "[17]\tvalid_0's l1: 0.488978\tvalid_0's binary_logloss: 0.676451\n",
      "[18]\tvalid_0's l1: 0.488478\tvalid_0's binary_logloss: 0.676471\n",
      "[19]\tvalid_0's l1: 0.488142\tvalid_0's binary_logloss: 0.676025\n",
      "[20]\tvalid_0's l1: 0.487432\tvalid_0's binary_logloss: 0.675907\n",
      "[21]\tvalid_0's l1: 0.48683\tvalid_0's binary_logloss: 0.674612\n",
      "[22]\tvalid_0's l1: 0.486058\tvalid_0's binary_logloss: 0.673422\n",
      "[23]\tvalid_0's l1: 0.485656\tvalid_0's binary_logloss: 0.674257\n",
      "[24]\tvalid_0's l1: 0.485803\tvalid_0's binary_logloss: 0.675175\n",
      "[25]\tvalid_0's l1: 0.485389\tvalid_0's binary_logloss: 0.675015\n",
      "[26]\tvalid_0's l1: 0.485002\tvalid_0's binary_logloss: 0.675581\n",
      "[27]\tvalid_0's l1: 0.484678\tvalid_0's binary_logloss: 0.675261\n",
      "Early stopping, best iteration is:\n",
      "[22]\tvalid_0's l1: 0.486058\tvalid_0's binary_logloss: 0.673422\n",
      "[1]\tvalid_0's l1: 0.500676\tvalid_0's binary_logloss: 0.69501\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.499976\tvalid_0's binary_logloss: 0.693718\n",
      "[3]\tvalid_0's l1: 0.500038\tvalid_0's binary_logloss: 0.69391\n",
      "[4]\tvalid_0's l1: 0.500051\tvalid_0's binary_logloss: 0.694254\n",
      "[5]\tvalid_0's l1: 0.499975\tvalid_0's binary_logloss: 0.694351\n",
      "[6]\tvalid_0's l1: 0.499803\tvalid_0's binary_logloss: 0.694391\n",
      "[7]\tvalid_0's l1: 0.499577\tvalid_0's binary_logloss: 0.694341\n",
      "Early stopping, best iteration is:\n",
      "[2]\tvalid_0's l1: 0.499976\tvalid_0's binary_logloss: 0.693718\n",
      "[1]\tvalid_0's l1: 0.499841\tvalid_0's binary_logloss: 0.69327\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.498341\tvalid_0's binary_logloss: 0.690479\n",
      "[3]\tvalid_0's l1: 0.498144\tvalid_0's binary_logloss: 0.690543\n",
      "[4]\tvalid_0's l1: 0.498074\tvalid_0's binary_logloss: 0.690916\n",
      "[5]\tvalid_0's l1: 0.496927\tvalid_0's binary_logloss: 0.689454\n",
      "[6]\tvalid_0's l1: 0.497087\tvalid_0's binary_logloss: 0.690131\n",
      "[7]\tvalid_0's l1: 0.497153\tvalid_0's binary_logloss: 0.691103\n",
      "[8]\tvalid_0's l1: 0.496512\tvalid_0's binary_logloss: 0.690333\n",
      "[9]\tvalid_0's l1: 0.495506\tvalid_0's binary_logloss: 0.689246\n",
      "[10]\tvalid_0's l1: 0.49431\tvalid_0's binary_logloss: 0.687873\n",
      "[11]\tvalid_0's l1: 0.494024\tvalid_0's binary_logloss: 0.687935\n",
      "[12]\tvalid_0's l1: 0.492861\tvalid_0's binary_logloss: 0.686658\n",
      "[13]\tvalid_0's l1: 0.493037\tvalid_0's binary_logloss: 0.687808\n",
      "[14]\tvalid_0's l1: 0.493684\tvalid_0's binary_logloss: 0.690564\n",
      "[15]\tvalid_0's l1: 0.494209\tvalid_0's binary_logloss: 0.69307\n",
      "[16]\tvalid_0's l1: 0.494729\tvalid_0's binary_logloss: 0.695784\n",
      "[17]\tvalid_0's l1: 0.494532\tvalid_0's binary_logloss: 0.696528\n",
      "Early stopping, best iteration is:\n",
      "[12]\tvalid_0's l1: 0.492861\tvalid_0's binary_logloss: 0.686658\n",
      "[1]\tvalid_0's l1: 0.500584\tvalid_0's binary_logloss: 0.694883\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500123\tvalid_0's binary_logloss: 0.694204\n",
      "[3]\tvalid_0's l1: 0.499469\tvalid_0's binary_logloss: 0.693446\n",
      "[4]\tvalid_0's l1: 0.498243\tvalid_0's binary_logloss: 0.691748\n",
      "[5]\tvalid_0's l1: 0.497858\tvalid_0's binary_logloss: 0.691258\n",
      "[6]\tvalid_0's l1: 0.496607\tvalid_0's binary_logloss: 0.689959\n",
      "[7]\tvalid_0's l1: 0.495836\tvalid_0's binary_logloss: 0.689488\n",
      "[8]\tvalid_0's l1: 0.494407\tvalid_0's binary_logloss: 0.688408\n",
      "[9]\tvalid_0's l1: 0.493904\tvalid_0's binary_logloss: 0.68816\n",
      "[10]\tvalid_0's l1: 0.493292\tvalid_0's binary_logloss: 0.68791\n",
      "[11]\tvalid_0's l1: 0.492952\tvalid_0's binary_logloss: 0.689128\n",
      "[12]\tvalid_0's l1: 0.492689\tvalid_0's binary_logloss: 0.689758\n",
      "[13]\tvalid_0's l1: 0.492135\tvalid_0's binary_logloss: 0.69076\n",
      "[14]\tvalid_0's l1: 0.491999\tvalid_0's binary_logloss: 0.691995\n",
      "[15]\tvalid_0's l1: 0.491614\tvalid_0's binary_logloss: 0.693189\n",
      "Early stopping, best iteration is:\n",
      "[10]\tvalid_0's l1: 0.493292\tvalid_0's binary_logloss: 0.68791\n",
      "[1]\tvalid_0's l1: 0.499873\tvalid_0's binary_logloss: 0.693842\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.498368\tvalid_0's binary_logloss: 0.691546\n",
      "[3]\tvalid_0's l1: 0.496842\tvalid_0's binary_logloss: 0.68947\n",
      "[4]\tvalid_0's l1: 0.496215\tvalid_0's binary_logloss: 0.688619\n",
      "[5]\tvalid_0's l1: 0.495438\tvalid_0's binary_logloss: 0.688266\n",
      "[6]\tvalid_0's l1: 0.494569\tvalid_0's binary_logloss: 0.686886\n",
      "[7]\tvalid_0's l1: 0.494049\tvalid_0's binary_logloss: 0.686528\n",
      "[8]\tvalid_0's l1: 0.4935\tvalid_0's binary_logloss: 0.686414\n",
      "[9]\tvalid_0's l1: 0.4923\tvalid_0's binary_logloss: 0.684783\n",
      "[10]\tvalid_0's l1: 0.491505\tvalid_0's binary_logloss: 0.683958\n",
      "[11]\tvalid_0's l1: 0.490807\tvalid_0's binary_logloss: 0.683884\n",
      "[12]\tvalid_0's l1: 0.488958\tvalid_0's binary_logloss: 0.681472\n",
      "[13]\tvalid_0's l1: 0.488366\tvalid_0's binary_logloss: 0.681951\n",
      "[14]\tvalid_0's l1: 0.487311\tvalid_0's binary_logloss: 0.681311\n",
      "[15]\tvalid_0's l1: 0.486386\tvalid_0's binary_logloss: 0.680763\n",
      "[16]\tvalid_0's l1: 0.485519\tvalid_0's binary_logloss: 0.680267\n",
      "[17]\tvalid_0's l1: 0.485044\tvalid_0's binary_logloss: 0.680816\n",
      "[18]\tvalid_0's l1: 0.48421\tvalid_0's binary_logloss: 0.679634\n",
      "[19]\tvalid_0's l1: 0.48439\tvalid_0's binary_logloss: 0.681119\n",
      "[20]\tvalid_0's l1: 0.484065\tvalid_0's binary_logloss: 0.68129\n",
      "[21]\tvalid_0's l1: 0.483398\tvalid_0's binary_logloss: 0.681332\n",
      "[22]\tvalid_0's l1: 0.483354\tvalid_0's binary_logloss: 0.682364\n",
      "[23]\tvalid_0's l1: 0.483411\tvalid_0's binary_logloss: 0.684782\n",
      "Early stopping, best iteration is:\n",
      "[18]\tvalid_0's l1: 0.48421\tvalid_0's binary_logloss: 0.679634\n",
      "[1]\tvalid_0's l1: 0.500425\tvalid_0's binary_logloss: 0.694526\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.499146\tvalid_0's binary_logloss: 0.692013\n",
      "[3]\tvalid_0's l1: 0.497938\tvalid_0's binary_logloss: 0.68962\n",
      "[4]\tvalid_0's l1: 0.497596\tvalid_0's binary_logloss: 0.689048\n",
      "[5]\tvalid_0's l1: 0.496723\tvalid_0's binary_logloss: 0.687576\n",
      "[6]\tvalid_0's l1: 0.496399\tvalid_0's binary_logloss: 0.687076\n",
      "[7]\tvalid_0's l1: 0.495396\tvalid_0's binary_logloss: 0.68544\n",
      "[8]\tvalid_0's l1: 0.494297\tvalid_0's binary_logloss: 0.683625\n",
      "[9]\tvalid_0's l1: 0.492936\tvalid_0's binary_logloss: 0.681283\n",
      "[10]\tvalid_0's l1: 0.492053\tvalid_0's binary_logloss: 0.680088\n",
      "[11]\tvalid_0's l1: 0.491426\tvalid_0's binary_logloss: 0.678964\n",
      "[12]\tvalid_0's l1: 0.491487\tvalid_0's binary_logloss: 0.67921\n",
      "[13]\tvalid_0's l1: 0.491273\tvalid_0's binary_logloss: 0.679008\n",
      "[14]\tvalid_0's l1: 0.490748\tvalid_0's binary_logloss: 0.678504\n",
      "[15]\tvalid_0's l1: 0.489916\tvalid_0's binary_logloss: 0.677785\n",
      "[16]\tvalid_0's l1: 0.489818\tvalid_0's binary_logloss: 0.677849\n",
      "[17]\tvalid_0's l1: 0.488978\tvalid_0's binary_logloss: 0.676451\n",
      "[18]\tvalid_0's l1: 0.488478\tvalid_0's binary_logloss: 0.676471\n",
      "[19]\tvalid_0's l1: 0.488142\tvalid_0's binary_logloss: 0.676025\n",
      "[20]\tvalid_0's l1: 0.487432\tvalid_0's binary_logloss: 0.675907\n",
      "[21]\tvalid_0's l1: 0.48683\tvalid_0's binary_logloss: 0.674612\n",
      "[22]\tvalid_0's l1: 0.486058\tvalid_0's binary_logloss: 0.673422\n",
      "[23]\tvalid_0's l1: 0.485656\tvalid_0's binary_logloss: 0.674257\n",
      "[24]\tvalid_0's l1: 0.485803\tvalid_0's binary_logloss: 0.675175\n",
      "[25]\tvalid_0's l1: 0.485389\tvalid_0's binary_logloss: 0.675015\n",
      "[26]\tvalid_0's l1: 0.485002\tvalid_0's binary_logloss: 0.675581\n",
      "[27]\tvalid_0's l1: 0.484678\tvalid_0's binary_logloss: 0.675261\n",
      "Early stopping, best iteration is:\n",
      "[22]\tvalid_0's l1: 0.486058\tvalid_0's binary_logloss: 0.673422\n",
      "[1]\tvalid_0's l1: 0.500676\tvalid_0's binary_logloss: 0.69501\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.499976\tvalid_0's binary_logloss: 0.693718\n",
      "[3]\tvalid_0's l1: 0.500038\tvalid_0's binary_logloss: 0.69391\n",
      "[4]\tvalid_0's l1: 0.500051\tvalid_0's binary_logloss: 0.694254\n",
      "[5]\tvalid_0's l1: 0.499975\tvalid_0's binary_logloss: 0.694351\n",
      "[6]\tvalid_0's l1: 0.499803\tvalid_0's binary_logloss: 0.694391\n",
      "[7]\tvalid_0's l1: 0.499577\tvalid_0's binary_logloss: 0.694341\n",
      "Early stopping, best iteration is:\n",
      "[2]\tvalid_0's l1: 0.499976\tvalid_0's binary_logloss: 0.693718\n",
      "[1]\tvalid_0's l1: 0.499841\tvalid_0's binary_logloss: 0.69327\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.498341\tvalid_0's binary_logloss: 0.690479\n",
      "[3]\tvalid_0's l1: 0.498144\tvalid_0's binary_logloss: 0.690543\n",
      "[4]\tvalid_0's l1: 0.498074\tvalid_0's binary_logloss: 0.690916\n",
      "[5]\tvalid_0's l1: 0.496927\tvalid_0's binary_logloss: 0.689454\n",
      "[6]\tvalid_0's l1: 0.497087\tvalid_0's binary_logloss: 0.690131\n",
      "[7]\tvalid_0's l1: 0.497153\tvalid_0's binary_logloss: 0.691103\n",
      "[8]\tvalid_0's l1: 0.496512\tvalid_0's binary_logloss: 0.690333\n",
      "[9]\tvalid_0's l1: 0.495506\tvalid_0's binary_logloss: 0.689246\n",
      "[10]\tvalid_0's l1: 0.49431\tvalid_0's binary_logloss: 0.687873\n",
      "[11]\tvalid_0's l1: 0.494024\tvalid_0's binary_logloss: 0.687935\n",
      "[12]\tvalid_0's l1: 0.492861\tvalid_0's binary_logloss: 0.686658\n",
      "[13]\tvalid_0's l1: 0.493037\tvalid_0's binary_logloss: 0.687808\n",
      "[14]\tvalid_0's l1: 0.493684\tvalid_0's binary_logloss: 0.690564\n",
      "[15]\tvalid_0's l1: 0.494209\tvalid_0's binary_logloss: 0.69307\n",
      "[16]\tvalid_0's l1: 0.494729\tvalid_0's binary_logloss: 0.695784\n",
      "[17]\tvalid_0's l1: 0.494532\tvalid_0's binary_logloss: 0.696528\n",
      "Early stopping, best iteration is:\n",
      "[12]\tvalid_0's l1: 0.492861\tvalid_0's binary_logloss: 0.686658\n",
      "[1]\tvalid_0's l1: 0.500584\tvalid_0's binary_logloss: 0.694883\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500123\tvalid_0's binary_logloss: 0.694204\n",
      "[3]\tvalid_0's l1: 0.499469\tvalid_0's binary_logloss: 0.693446\n",
      "[4]\tvalid_0's l1: 0.498243\tvalid_0's binary_logloss: 0.691748\n",
      "[5]\tvalid_0's l1: 0.497858\tvalid_0's binary_logloss: 0.691258\n",
      "[6]\tvalid_0's l1: 0.496607\tvalid_0's binary_logloss: 0.689959\n",
      "[7]\tvalid_0's l1: 0.495836\tvalid_0's binary_logloss: 0.689488\n",
      "[8]\tvalid_0's l1: 0.494407\tvalid_0's binary_logloss: 0.688408\n",
      "[9]\tvalid_0's l1: 0.493904\tvalid_0's binary_logloss: 0.68816\n",
      "[10]\tvalid_0's l1: 0.493292\tvalid_0's binary_logloss: 0.68791\n",
      "[11]\tvalid_0's l1: 0.492952\tvalid_0's binary_logloss: 0.689128\n",
      "[12]\tvalid_0's l1: 0.492689\tvalid_0's binary_logloss: 0.689758\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[13]\tvalid_0's l1: 0.492135\tvalid_0's binary_logloss: 0.69076\n",
      "[14]\tvalid_0's l1: 0.491999\tvalid_0's binary_logloss: 0.691995\n",
      "[15]\tvalid_0's l1: 0.491614\tvalid_0's binary_logloss: 0.693189\n",
      "Early stopping, best iteration is:\n",
      "[10]\tvalid_0's l1: 0.493292\tvalid_0's binary_logloss: 0.68791\n",
      "[1]\tvalid_0's l1: 0.499873\tvalid_0's binary_logloss: 0.693842\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.498368\tvalid_0's binary_logloss: 0.691546\n",
      "[3]\tvalid_0's l1: 0.496842\tvalid_0's binary_logloss: 0.68947\n",
      "[4]\tvalid_0's l1: 0.496215\tvalid_0's binary_logloss: 0.688619\n",
      "[5]\tvalid_0's l1: 0.495438\tvalid_0's binary_logloss: 0.688266\n",
      "[6]\tvalid_0's l1: 0.494569\tvalid_0's binary_logloss: 0.686886\n",
      "[7]\tvalid_0's l1: 0.494049\tvalid_0's binary_logloss: 0.686528\n",
      "[8]\tvalid_0's l1: 0.4935\tvalid_0's binary_logloss: 0.686414\n",
      "[9]\tvalid_0's l1: 0.4923\tvalid_0's binary_logloss: 0.684783\n",
      "[10]\tvalid_0's l1: 0.491505\tvalid_0's binary_logloss: 0.683958\n",
      "[11]\tvalid_0's l1: 0.490807\tvalid_0's binary_logloss: 0.683884\n",
      "[12]\tvalid_0's l1: 0.488958\tvalid_0's binary_logloss: 0.681472\n",
      "[13]\tvalid_0's l1: 0.488366\tvalid_0's binary_logloss: 0.681951\n",
      "[14]\tvalid_0's l1: 0.487311\tvalid_0's binary_logloss: 0.681311\n",
      "[15]\tvalid_0's l1: 0.486386\tvalid_0's binary_logloss: 0.680763\n",
      "[16]\tvalid_0's l1: 0.485519\tvalid_0's binary_logloss: 0.680267\n",
      "[17]\tvalid_0's l1: 0.485044\tvalid_0's binary_logloss: 0.680816\n",
      "[18]\tvalid_0's l1: 0.48421\tvalid_0's binary_logloss: 0.679634\n",
      "[19]\tvalid_0's l1: 0.48439\tvalid_0's binary_logloss: 0.681119\n",
      "[20]\tvalid_0's l1: 0.484065\tvalid_0's binary_logloss: 0.68129\n",
      "[21]\tvalid_0's l1: 0.483398\tvalid_0's binary_logloss: 0.681332\n",
      "[22]\tvalid_0's l1: 0.483354\tvalid_0's binary_logloss: 0.682364\n",
      "[23]\tvalid_0's l1: 0.483411\tvalid_0's binary_logloss: 0.684782\n",
      "Early stopping, best iteration is:\n",
      "[18]\tvalid_0's l1: 0.48421\tvalid_0's binary_logloss: 0.679634\n",
      "[1]\tvalid_0's l1: 0.500425\tvalid_0's binary_logloss: 0.694526\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.499146\tvalid_0's binary_logloss: 0.692013\n",
      "[3]\tvalid_0's l1: 0.497938\tvalid_0's binary_logloss: 0.68962\n",
      "[4]\tvalid_0's l1: 0.497596\tvalid_0's binary_logloss: 0.689048\n",
      "[5]\tvalid_0's l1: 0.496723\tvalid_0's binary_logloss: 0.687576\n",
      "[6]\tvalid_0's l1: 0.496399\tvalid_0's binary_logloss: 0.687076\n",
      "[7]\tvalid_0's l1: 0.495396\tvalid_0's binary_logloss: 0.68544\n",
      "[8]\tvalid_0's l1: 0.494297\tvalid_0's binary_logloss: 0.683625\n",
      "[9]\tvalid_0's l1: 0.492936\tvalid_0's binary_logloss: 0.681283\n",
      "[10]\tvalid_0's l1: 0.492053\tvalid_0's binary_logloss: 0.680088\n",
      "[11]\tvalid_0's l1: 0.491426\tvalid_0's binary_logloss: 0.678964\n",
      "[12]\tvalid_0's l1: 0.491487\tvalid_0's binary_logloss: 0.67921\n",
      "[13]\tvalid_0's l1: 0.491273\tvalid_0's binary_logloss: 0.679008\n",
      "[14]\tvalid_0's l1: 0.490748\tvalid_0's binary_logloss: 0.678504\n",
      "[15]\tvalid_0's l1: 0.489916\tvalid_0's binary_logloss: 0.677785\n",
      "[16]\tvalid_0's l1: 0.489818\tvalid_0's binary_logloss: 0.677849\n",
      "[17]\tvalid_0's l1: 0.488978\tvalid_0's binary_logloss: 0.676451\n",
      "[18]\tvalid_0's l1: 0.488478\tvalid_0's binary_logloss: 0.676471\n",
      "[19]\tvalid_0's l1: 0.488142\tvalid_0's binary_logloss: 0.676025\n",
      "[20]\tvalid_0's l1: 0.487432\tvalid_0's binary_logloss: 0.675907\n",
      "[21]\tvalid_0's l1: 0.48683\tvalid_0's binary_logloss: 0.674612\n",
      "[22]\tvalid_0's l1: 0.486058\tvalid_0's binary_logloss: 0.673422\n",
      "[23]\tvalid_0's l1: 0.485656\tvalid_0's binary_logloss: 0.674257\n",
      "[24]\tvalid_0's l1: 0.485803\tvalid_0's binary_logloss: 0.675175\n",
      "[25]\tvalid_0's l1: 0.485389\tvalid_0's binary_logloss: 0.675015\n",
      "[26]\tvalid_0's l1: 0.485002\tvalid_0's binary_logloss: 0.675581\n",
      "[27]\tvalid_0's l1: 0.484678\tvalid_0's binary_logloss: 0.675261\n",
      "Early stopping, best iteration is:\n",
      "[22]\tvalid_0's l1: 0.486058\tvalid_0's binary_logloss: 0.673422\n",
      "[1]\tvalid_0's l1: 0.500676\tvalid_0's binary_logloss: 0.69501\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.499976\tvalid_0's binary_logloss: 0.693718\n",
      "[3]\tvalid_0's l1: 0.500038\tvalid_0's binary_logloss: 0.69391\n",
      "[4]\tvalid_0's l1: 0.500051\tvalid_0's binary_logloss: 0.694254\n",
      "[5]\tvalid_0's l1: 0.499975\tvalid_0's binary_logloss: 0.694351\n",
      "[6]\tvalid_0's l1: 0.499803\tvalid_0's binary_logloss: 0.694391\n",
      "[7]\tvalid_0's l1: 0.499577\tvalid_0's binary_logloss: 0.694341\n",
      "Early stopping, best iteration is:\n",
      "[2]\tvalid_0's l1: 0.499976\tvalid_0's binary_logloss: 0.693718\n",
      "[1]\tvalid_0's l1: 0.499841\tvalid_0's binary_logloss: 0.69327\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.498341\tvalid_0's binary_logloss: 0.690479\n",
      "[3]\tvalid_0's l1: 0.498144\tvalid_0's binary_logloss: 0.690543\n",
      "[4]\tvalid_0's l1: 0.498074\tvalid_0's binary_logloss: 0.690916\n",
      "[5]\tvalid_0's l1: 0.496927\tvalid_0's binary_logloss: 0.689454\n",
      "[6]\tvalid_0's l1: 0.497087\tvalid_0's binary_logloss: 0.690131\n",
      "[7]\tvalid_0's l1: 0.497153\tvalid_0's binary_logloss: 0.691103\n",
      "[8]\tvalid_0's l1: 0.496512\tvalid_0's binary_logloss: 0.690333\n",
      "[9]\tvalid_0's l1: 0.495506\tvalid_0's binary_logloss: 0.689246\n",
      "[10]\tvalid_0's l1: 0.49431\tvalid_0's binary_logloss: 0.687873\n",
      "[11]\tvalid_0's l1: 0.494024\tvalid_0's binary_logloss: 0.687935\n",
      "[12]\tvalid_0's l1: 0.492861\tvalid_0's binary_logloss: 0.686658\n",
      "[13]\tvalid_0's l1: 0.493037\tvalid_0's binary_logloss: 0.687808\n",
      "[14]\tvalid_0's l1: 0.493684\tvalid_0's binary_logloss: 0.690564\n",
      "[15]\tvalid_0's l1: 0.494209\tvalid_0's binary_logloss: 0.69307\n",
      "[16]\tvalid_0's l1: 0.494729\tvalid_0's binary_logloss: 0.695784\n",
      "[17]\tvalid_0's l1: 0.494532\tvalid_0's binary_logloss: 0.696528\n",
      "Early stopping, best iteration is:\n",
      "[12]\tvalid_0's l1: 0.492861\tvalid_0's binary_logloss: 0.686658\n",
      "[1]\tvalid_0's l1: 0.500584\tvalid_0's binary_logloss: 0.694883\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500123\tvalid_0's binary_logloss: 0.694204\n",
      "[3]\tvalid_0's l1: 0.499469\tvalid_0's binary_logloss: 0.693446\n",
      "[4]\tvalid_0's l1: 0.498243\tvalid_0's binary_logloss: 0.691748\n",
      "[5]\tvalid_0's l1: 0.497858\tvalid_0's binary_logloss: 0.691258\n",
      "[6]\tvalid_0's l1: 0.496607\tvalid_0's binary_logloss: 0.689959\n",
      "[7]\tvalid_0's l1: 0.495836\tvalid_0's binary_logloss: 0.689488\n",
      "[8]\tvalid_0's l1: 0.494407\tvalid_0's binary_logloss: 0.688408\n",
      "[9]\tvalid_0's l1: 0.493904\tvalid_0's binary_logloss: 0.68816\n",
      "[10]\tvalid_0's l1: 0.493292\tvalid_0's binary_logloss: 0.68791\n",
      "[11]\tvalid_0's l1: 0.492952\tvalid_0's binary_logloss: 0.689128\n",
      "[12]\tvalid_0's l1: 0.492689\tvalid_0's binary_logloss: 0.689758\n",
      "[13]\tvalid_0's l1: 0.492135\tvalid_0's binary_logloss: 0.69076\n",
      "[14]\tvalid_0's l1: 0.491999\tvalid_0's binary_logloss: 0.691995\n",
      "[15]\tvalid_0's l1: 0.491614\tvalid_0's binary_logloss: 0.693189\n",
      "Early stopping, best iteration is:\n",
      "[10]\tvalid_0's l1: 0.493292\tvalid_0's binary_logloss: 0.68791\n",
      "[1]\tvalid_0's l1: 0.499873\tvalid_0's binary_logloss: 0.693842\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.498368\tvalid_0's binary_logloss: 0.691546\n",
      "[3]\tvalid_0's l1: 0.496842\tvalid_0's binary_logloss: 0.68947\n",
      "[4]\tvalid_0's l1: 0.496215\tvalid_0's binary_logloss: 0.688619\n",
      "[5]\tvalid_0's l1: 0.495438\tvalid_0's binary_logloss: 0.688266\n",
      "[6]\tvalid_0's l1: 0.494569\tvalid_0's binary_logloss: 0.686886\n",
      "[7]\tvalid_0's l1: 0.494049\tvalid_0's binary_logloss: 0.686528\n",
      "[8]\tvalid_0's l1: 0.4935\tvalid_0's binary_logloss: 0.686414\n",
      "[9]\tvalid_0's l1: 0.4923\tvalid_0's binary_logloss: 0.684783\n",
      "[10]\tvalid_0's l1: 0.491505\tvalid_0's binary_logloss: 0.683958\n",
      "[11]\tvalid_0's l1: 0.490807\tvalid_0's binary_logloss: 0.683884\n",
      "[12]\tvalid_0's l1: 0.488958\tvalid_0's binary_logloss: 0.681472\n",
      "[13]\tvalid_0's l1: 0.488366\tvalid_0's binary_logloss: 0.681951\n",
      "[14]\tvalid_0's l1: 0.487311\tvalid_0's binary_logloss: 0.681311\n",
      "[15]\tvalid_0's l1: 0.486386\tvalid_0's binary_logloss: 0.680763\n",
      "[16]\tvalid_0's l1: 0.485519\tvalid_0's binary_logloss: 0.680267\n",
      "[17]\tvalid_0's l1: 0.485044\tvalid_0's binary_logloss: 0.680816\n",
      "[18]\tvalid_0's l1: 0.48421\tvalid_0's binary_logloss: 0.679634\n",
      "[19]\tvalid_0's l1: 0.48439\tvalid_0's binary_logloss: 0.681119\n",
      "[20]\tvalid_0's l1: 0.484065\tvalid_0's binary_logloss: 0.68129\n",
      "[21]\tvalid_0's l1: 0.483398\tvalid_0's binary_logloss: 0.681332\n",
      "[22]\tvalid_0's l1: 0.483354\tvalid_0's binary_logloss: 0.682364\n",
      "[23]\tvalid_0's l1: 0.483411\tvalid_0's binary_logloss: 0.684782\n",
      "Early stopping, best iteration is:\n",
      "[18]\tvalid_0's l1: 0.48421\tvalid_0's binary_logloss: 0.679634\n",
      "[1]\tvalid_0's l1: 0.500425\tvalid_0's binary_logloss: 0.694526\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.499146\tvalid_0's binary_logloss: 0.692013\n",
      "[3]\tvalid_0's l1: 0.497938\tvalid_0's binary_logloss: 0.68962\n",
      "[4]\tvalid_0's l1: 0.497596\tvalid_0's binary_logloss: 0.689048\n",
      "[5]\tvalid_0's l1: 0.496723\tvalid_0's binary_logloss: 0.687576\n",
      "[6]\tvalid_0's l1: 0.496399\tvalid_0's binary_logloss: 0.687076\n",
      "[7]\tvalid_0's l1: 0.495396\tvalid_0's binary_logloss: 0.68544\n",
      "[8]\tvalid_0's l1: 0.494297\tvalid_0's binary_logloss: 0.683625\n",
      "[9]\tvalid_0's l1: 0.492936\tvalid_0's binary_logloss: 0.681283\n",
      "[10]\tvalid_0's l1: 0.492053\tvalid_0's binary_logloss: 0.680088\n",
      "[11]\tvalid_0's l1: 0.491426\tvalid_0's binary_logloss: 0.678964\n",
      "[12]\tvalid_0's l1: 0.491487\tvalid_0's binary_logloss: 0.67921\n",
      "[13]\tvalid_0's l1: 0.491273\tvalid_0's binary_logloss: 0.679008\n",
      "[14]\tvalid_0's l1: 0.490748\tvalid_0's binary_logloss: 0.678504\n",
      "[15]\tvalid_0's l1: 0.489916\tvalid_0's binary_logloss: 0.677785\n",
      "[16]\tvalid_0's l1: 0.489818\tvalid_0's binary_logloss: 0.677849\n",
      "[17]\tvalid_0's l1: 0.488978\tvalid_0's binary_logloss: 0.676451\n",
      "[18]\tvalid_0's l1: 0.488478\tvalid_0's binary_logloss: 0.676471\n",
      "[19]\tvalid_0's l1: 0.488142\tvalid_0's binary_logloss: 0.676025\n",
      "[20]\tvalid_0's l1: 0.487432\tvalid_0's binary_logloss: 0.675907\n",
      "[21]\tvalid_0's l1: 0.48683\tvalid_0's binary_logloss: 0.674612\n",
      "[22]\tvalid_0's l1: 0.486058\tvalid_0's binary_logloss: 0.673422\n",
      "[23]\tvalid_0's l1: 0.485656\tvalid_0's binary_logloss: 0.674257\n",
      "[24]\tvalid_0's l1: 0.485803\tvalid_0's binary_logloss: 0.675175\n",
      "[25]\tvalid_0's l1: 0.485389\tvalid_0's binary_logloss: 0.675015\n",
      "[26]\tvalid_0's l1: 0.485002\tvalid_0's binary_logloss: 0.675581\n",
      "[27]\tvalid_0's l1: 0.484678\tvalid_0's binary_logloss: 0.675261\n",
      "Early stopping, best iteration is:\n",
      "[22]\tvalid_0's l1: 0.486058\tvalid_0's binary_logloss: 0.673422\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1]\tvalid_0's l1: 0.500676\tvalid_0's binary_logloss: 0.69501\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.499976\tvalid_0's binary_logloss: 0.693718\n",
      "[3]\tvalid_0's l1: 0.500038\tvalid_0's binary_logloss: 0.69391\n",
      "[4]\tvalid_0's l1: 0.500051\tvalid_0's binary_logloss: 0.694254\n",
      "[5]\tvalid_0's l1: 0.499975\tvalid_0's binary_logloss: 0.694351\n",
      "[6]\tvalid_0's l1: 0.499803\tvalid_0's binary_logloss: 0.694391\n",
      "[7]\tvalid_0's l1: 0.499577\tvalid_0's binary_logloss: 0.694341\n",
      "Early stopping, best iteration is:\n",
      "[2]\tvalid_0's l1: 0.499976\tvalid_0's binary_logloss: 0.693718\n",
      "[1]\tvalid_0's l1: 0.499841\tvalid_0's binary_logloss: 0.69327\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.498341\tvalid_0's binary_logloss: 0.690479\n",
      "[3]\tvalid_0's l1: 0.498144\tvalid_0's binary_logloss: 0.690543\n",
      "[4]\tvalid_0's l1: 0.498074\tvalid_0's binary_logloss: 0.690916\n",
      "[5]\tvalid_0's l1: 0.496927\tvalid_0's binary_logloss: 0.689454\n",
      "[6]\tvalid_0's l1: 0.497087\tvalid_0's binary_logloss: 0.690131\n",
      "[7]\tvalid_0's l1: 0.497153\tvalid_0's binary_logloss: 0.691103\n",
      "[8]\tvalid_0's l1: 0.496512\tvalid_0's binary_logloss: 0.690333\n",
      "[9]\tvalid_0's l1: 0.495506\tvalid_0's binary_logloss: 0.689246\n",
      "[10]\tvalid_0's l1: 0.49431\tvalid_0's binary_logloss: 0.687873\n",
      "[11]\tvalid_0's l1: 0.494024\tvalid_0's binary_logloss: 0.687935\n",
      "[12]\tvalid_0's l1: 0.492861\tvalid_0's binary_logloss: 0.686658\n",
      "[13]\tvalid_0's l1: 0.493037\tvalid_0's binary_logloss: 0.687808\n",
      "[14]\tvalid_0's l1: 0.493684\tvalid_0's binary_logloss: 0.690564\n",
      "[15]\tvalid_0's l1: 0.494209\tvalid_0's binary_logloss: 0.69307\n",
      "[16]\tvalid_0's l1: 0.494729\tvalid_0's binary_logloss: 0.695784\n",
      "[17]\tvalid_0's l1: 0.494532\tvalid_0's binary_logloss: 0.696528\n",
      "Early stopping, best iteration is:\n",
      "[12]\tvalid_0's l1: 0.492861\tvalid_0's binary_logloss: 0.686658\n",
      "[1]\tvalid_0's l1: 0.500739\tvalid_0's binary_logloss: 0.695374\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500217\tvalid_0's binary_logloss: 0.694564\n",
      "[3]\tvalid_0's l1: 0.499029\tvalid_0's binary_logloss: 0.692877\n",
      "[4]\tvalid_0's l1: 0.498692\tvalid_0's binary_logloss: 0.692415\n",
      "[5]\tvalid_0's l1: 0.498085\tvalid_0's binary_logloss: 0.692408\n",
      "[6]\tvalid_0's l1: 0.497231\tvalid_0's binary_logloss: 0.691042\n",
      "[7]\tvalid_0's l1: 0.497168\tvalid_0's binary_logloss: 0.692276\n",
      "[8]\tvalid_0's l1: 0.495817\tvalid_0's binary_logloss: 0.690593\n",
      "[9]\tvalid_0's l1: 0.494405\tvalid_0's binary_logloss: 0.689587\n",
      "[10]\tvalid_0's l1: 0.494029\tvalid_0's binary_logloss: 0.689746\n",
      "[11]\tvalid_0's l1: 0.493069\tvalid_0's binary_logloss: 0.689636\n",
      "[12]\tvalid_0's l1: 0.491902\tvalid_0's binary_logloss: 0.689261\n",
      "[13]\tvalid_0's l1: 0.491086\tvalid_0's binary_logloss: 0.688831\n",
      "[14]\tvalid_0's l1: 0.490831\tvalid_0's binary_logloss: 0.690531\n",
      "[15]\tvalid_0's l1: 0.490364\tvalid_0's binary_logloss: 0.690282\n",
      "[16]\tvalid_0's l1: 0.490603\tvalid_0's binary_logloss: 0.692082\n",
      "[17]\tvalid_0's l1: 0.490198\tvalid_0's binary_logloss: 0.693997\n",
      "[18]\tvalid_0's l1: 0.490106\tvalid_0's binary_logloss: 0.695334\n",
      "Early stopping, best iteration is:\n",
      "[13]\tvalid_0's l1: 0.491086\tvalid_0's binary_logloss: 0.688831\n",
      "[1]\tvalid_0's l1: 0.499797\tvalid_0's binary_logloss: 0.693815\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.498252\tvalid_0's binary_logloss: 0.691487\n",
      "[3]\tvalid_0's l1: 0.496713\tvalid_0's binary_logloss: 0.689454\n",
      "[4]\tvalid_0's l1: 0.495844\tvalid_0's binary_logloss: 0.688474\n",
      "[5]\tvalid_0's l1: 0.495091\tvalid_0's binary_logloss: 0.688216\n",
      "[6]\tvalid_0's l1: 0.494663\tvalid_0's binary_logloss: 0.688387\n",
      "[7]\tvalid_0's l1: 0.494013\tvalid_0's binary_logloss: 0.687874\n",
      "[8]\tvalid_0's l1: 0.493153\tvalid_0's binary_logloss: 0.688006\n",
      "[9]\tvalid_0's l1: 0.493005\tvalid_0's binary_logloss: 0.689338\n",
      "[10]\tvalid_0's l1: 0.492912\tvalid_0's binary_logloss: 0.690043\n",
      "[11]\tvalid_0's l1: 0.491543\tvalid_0's binary_logloss: 0.688962\n",
      "[12]\tvalid_0's l1: 0.490459\tvalid_0's binary_logloss: 0.688999\n",
      "Early stopping, best iteration is:\n",
      "[7]\tvalid_0's l1: 0.494013\tvalid_0's binary_logloss: 0.687874\n",
      "[1]\tvalid_0's l1: 0.49998\tvalid_0's binary_logloss: 0.693805\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.498115\tvalid_0's binary_logloss: 0.690297\n",
      "[3]\tvalid_0's l1: 0.497681\tvalid_0's binary_logloss: 0.689521\n",
      "[4]\tvalid_0's l1: 0.49633\tvalid_0's binary_logloss: 0.687592\n",
      "[5]\tvalid_0's l1: 0.495405\tvalid_0's binary_logloss: 0.686081\n",
      "[6]\tvalid_0's l1: 0.494077\tvalid_0's binary_logloss: 0.684603\n",
      "[7]\tvalid_0's l1: 0.493777\tvalid_0's binary_logloss: 0.685006\n",
      "[8]\tvalid_0's l1: 0.493028\tvalid_0's binary_logloss: 0.68427\n",
      "[9]\tvalid_0's l1: 0.492093\tvalid_0's binary_logloss: 0.68256\n",
      "[10]\tvalid_0's l1: 0.490633\tvalid_0's binary_logloss: 0.68097\n",
      "[11]\tvalid_0's l1: 0.48917\tvalid_0's binary_logloss: 0.678713\n",
      "[12]\tvalid_0's l1: 0.488272\tvalid_0's binary_logloss: 0.677289\n",
      "[13]\tvalid_0's l1: 0.487393\tvalid_0's binary_logloss: 0.675807\n",
      "[14]\tvalid_0's l1: 0.486343\tvalid_0's binary_logloss: 0.674324\n",
      "[15]\tvalid_0's l1: 0.485867\tvalid_0's binary_logloss: 0.673972\n",
      "[16]\tvalid_0's l1: 0.485703\tvalid_0's binary_logloss: 0.67394\n",
      "[17]\tvalid_0's l1: 0.484869\tvalid_0's binary_logloss: 0.673044\n",
      "[18]\tvalid_0's l1: 0.483842\tvalid_0's binary_logloss: 0.672492\n",
      "[19]\tvalid_0's l1: 0.48355\tvalid_0's binary_logloss: 0.672442\n",
      "[20]\tvalid_0's l1: 0.482171\tvalid_0's binary_logloss: 0.67043\n",
      "[21]\tvalid_0's l1: 0.48214\tvalid_0's binary_logloss: 0.671283\n",
      "[22]\tvalid_0's l1: 0.481526\tvalid_0's binary_logloss: 0.670743\n",
      "[23]\tvalid_0's l1: 0.480885\tvalid_0's binary_logloss: 0.670321\n",
      "[24]\tvalid_0's l1: 0.479818\tvalid_0's binary_logloss: 0.669276\n",
      "[25]\tvalid_0's l1: 0.479672\tvalid_0's binary_logloss: 0.670102\n",
      "[26]\tvalid_0's l1: 0.478814\tvalid_0's binary_logloss: 0.669603\n",
      "[27]\tvalid_0's l1: 0.477851\tvalid_0's binary_logloss: 0.668546\n",
      "[28]\tvalid_0's l1: 0.477276\tvalid_0's binary_logloss: 0.667566\n",
      "[29]\tvalid_0's l1: 0.476935\tvalid_0's binary_logloss: 0.667372\n",
      "[30]\tvalid_0's l1: 0.476828\tvalid_0's binary_logloss: 0.668177\n",
      "[31]\tvalid_0's l1: 0.476465\tvalid_0's binary_logloss: 0.667519\n",
      "[32]\tvalid_0's l1: 0.475634\tvalid_0's binary_logloss: 0.666702\n",
      "[33]\tvalid_0's l1: 0.475327\tvalid_0's binary_logloss: 0.667471\n",
      "[34]\tvalid_0's l1: 0.474578\tvalid_0's binary_logloss: 0.666829\n",
      "[35]\tvalid_0's l1: 0.474819\tvalid_0's binary_logloss: 0.667748\n",
      "[36]\tvalid_0's l1: 0.474034\tvalid_0's binary_logloss: 0.666847\n",
      "[37]\tvalid_0's l1: 0.473523\tvalid_0's binary_logloss: 0.666575\n",
      "[38]\tvalid_0's l1: 0.473162\tvalid_0's binary_logloss: 0.66675\n",
      "[39]\tvalid_0's l1: 0.472691\tvalid_0's binary_logloss: 0.66603\n",
      "[40]\tvalid_0's l1: 0.472217\tvalid_0's binary_logloss: 0.665692\n",
      "[41]\tvalid_0's l1: 0.471943\tvalid_0's binary_logloss: 0.666622\n",
      "[42]\tvalid_0's l1: 0.471648\tvalid_0's binary_logloss: 0.665957\n",
      "[43]\tvalid_0's l1: 0.471382\tvalid_0's binary_logloss: 0.665157\n",
      "[44]\tvalid_0's l1: 0.471733\tvalid_0's binary_logloss: 0.666714\n",
      "[45]\tvalid_0's l1: 0.471541\tvalid_0's binary_logloss: 0.666641\n",
      "[46]\tvalid_0's l1: 0.471832\tvalid_0's binary_logloss: 0.666781\n",
      "[47]\tvalid_0's l1: 0.47139\tvalid_0's binary_logloss: 0.666713\n",
      "[48]\tvalid_0's l1: 0.470897\tvalid_0's binary_logloss: 0.665888\n",
      "Early stopping, best iteration is:\n",
      "[43]\tvalid_0's l1: 0.471382\tvalid_0's binary_logloss: 0.665157\n",
      "[1]\tvalid_0's l1: 0.500027\tvalid_0's binary_logloss: 0.693799\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.499582\tvalid_0's binary_logloss: 0.693072\n",
      "[3]\tvalid_0's l1: 0.499108\tvalid_0's binary_logloss: 0.692256\n",
      "[4]\tvalid_0's l1: 0.499481\tvalid_0's binary_logloss: 0.693495\n",
      "[5]\tvalid_0's l1: 0.499418\tvalid_0's binary_logloss: 0.694043\n",
      "[6]\tvalid_0's l1: 0.498864\tvalid_0's binary_logloss: 0.69381\n",
      "[7]\tvalid_0's l1: 0.498548\tvalid_0's binary_logloss: 0.694357\n",
      "[8]\tvalid_0's l1: 0.497925\tvalid_0's binary_logloss: 0.694231\n",
      "Early stopping, best iteration is:\n",
      "[3]\tvalid_0's l1: 0.499108\tvalid_0's binary_logloss: 0.692256\n",
      "[1]\tvalid_0's l1: 0.50024\tvalid_0's binary_logloss: 0.694202\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.49866\tvalid_0's binary_logloss: 0.6916\n",
      "[3]\tvalid_0's l1: 0.497466\tvalid_0's binary_logloss: 0.690118\n",
      "[4]\tvalid_0's l1: 0.496775\tvalid_0's binary_logloss: 0.689527\n",
      "[5]\tvalid_0's l1: 0.496603\tvalid_0's binary_logloss: 0.690456\n",
      "[6]\tvalid_0's l1: 0.49607\tvalid_0's binary_logloss: 0.69082\n",
      "[7]\tvalid_0's l1: 0.495731\tvalid_0's binary_logloss: 0.691306\n",
      "[8]\tvalid_0's l1: 0.494276\tvalid_0's binary_logloss: 0.690151\n",
      "[9]\tvalid_0's l1: 0.493837\tvalid_0's binary_logloss: 0.690852\n",
      "Early stopping, best iteration is:\n",
      "[4]\tvalid_0's l1: 0.496775\tvalid_0's binary_logloss: 0.689527\n",
      "[1]\tvalid_0's l1: 0.500739\tvalid_0's binary_logloss: 0.695375\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500217\tvalid_0's binary_logloss: 0.694566\n",
      "[3]\tvalid_0's l1: 0.499029\tvalid_0's binary_logloss: 0.692881\n",
      "[4]\tvalid_0's l1: 0.498693\tvalid_0's binary_logloss: 0.692418\n",
      "[5]\tvalid_0's l1: 0.498086\tvalid_0's binary_logloss: 0.692412\n",
      "[6]\tvalid_0's l1: 0.497232\tvalid_0's binary_logloss: 0.691046\n",
      "[7]\tvalid_0's l1: 0.497169\tvalid_0's binary_logloss: 0.69228\n",
      "[8]\tvalid_0's l1: 0.495819\tvalid_0's binary_logloss: 0.690597\n",
      "[9]\tvalid_0's l1: 0.494719\tvalid_0's binary_logloss: 0.690008\n",
      "[10]\tvalid_0's l1: 0.494339\tvalid_0's binary_logloss: 0.690112\n",
      "[11]\tvalid_0's l1: 0.49345\tvalid_0's binary_logloss: 0.690136\n",
      "[12]\tvalid_0's l1: 0.493034\tvalid_0's binary_logloss: 0.690399\n",
      "[13]\tvalid_0's l1: 0.492896\tvalid_0's binary_logloss: 0.69148\n",
      "[14]\tvalid_0's l1: 0.492481\tvalid_0's binary_logloss: 0.691332\n",
      "Early stopping, best iteration is:\n",
      "[9]\tvalid_0's l1: 0.494719\tvalid_0's binary_logloss: 0.690008\n",
      "[1]\tvalid_0's l1: 0.499683\tvalid_0's binary_logloss: 0.693595\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.498137\tvalid_0's binary_logloss: 0.691269\n",
      "[3]\tvalid_0's l1: 0.496383\tvalid_0's binary_logloss: 0.688867\n",
      "[4]\tvalid_0's l1: 0.495584\tvalid_0's binary_logloss: 0.688003\n",
      "[5]\tvalid_0's l1: 0.494702\tvalid_0's binary_logloss: 0.687454\n",
      "[6]\tvalid_0's l1: 0.49428\tvalid_0's binary_logloss: 0.687657\n",
      "[7]\tvalid_0's l1: 0.493633\tvalid_0's binary_logloss: 0.687194\n",
      "[8]\tvalid_0's l1: 0.492774\tvalid_0's binary_logloss: 0.687367\n",
      "[9]\tvalid_0's l1: 0.492631\tvalid_0's binary_logloss: 0.688723\n",
      "[10]\tvalid_0's l1: 0.492344\tvalid_0's binary_logloss: 0.689085\n",
      "[11]\tvalid_0's l1: 0.491101\tvalid_0's binary_logloss: 0.688175\n",
      "[12]\tvalid_0's l1: 0.490473\tvalid_0's binary_logloss: 0.689075\n",
      "Early stopping, best iteration is:\n",
      "[7]\tvalid_0's l1: 0.493633\tvalid_0's binary_logloss: 0.687194\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1]\tvalid_0's l1: 0.49998\tvalid_0's binary_logloss: 0.693805\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.497834\tvalid_0's binary_logloss: 0.689777\n",
      "[3]\tvalid_0's l1: 0.496964\tvalid_0's binary_logloss: 0.68825\n",
      "[4]\tvalid_0's l1: 0.495562\tvalid_0's binary_logloss: 0.686079\n",
      "[5]\tvalid_0's l1: 0.493892\tvalid_0's binary_logloss: 0.683593\n",
      "[6]\tvalid_0's l1: 0.493337\tvalid_0's binary_logloss: 0.683126\n",
      "[7]\tvalid_0's l1: 0.491981\tvalid_0's binary_logloss: 0.681505\n",
      "[8]\tvalid_0's l1: 0.49051\tvalid_0's binary_logloss: 0.678823\n",
      "[9]\tvalid_0's l1: 0.488975\tvalid_0's binary_logloss: 0.676579\n",
      "[10]\tvalid_0's l1: 0.489269\tvalid_0's binary_logloss: 0.677711\n",
      "[11]\tvalid_0's l1: 0.488243\tvalid_0's binary_logloss: 0.676685\n",
      "[12]\tvalid_0's l1: 0.488331\tvalid_0's binary_logloss: 0.677508\n",
      "[13]\tvalid_0's l1: 0.487504\tvalid_0's binary_logloss: 0.677646\n",
      "[14]\tvalid_0's l1: 0.487319\tvalid_0's binary_logloss: 0.67724\n",
      "Early stopping, best iteration is:\n",
      "[9]\tvalid_0's l1: 0.488975\tvalid_0's binary_logloss: 0.676579\n",
      "[1]\tvalid_0's l1: 0.500027\tvalid_0's binary_logloss: 0.693799\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.499582\tvalid_0's binary_logloss: 0.693072\n",
      "[3]\tvalid_0's l1: 0.499091\tvalid_0's binary_logloss: 0.692253\n",
      "[4]\tvalid_0's l1: 0.499462\tvalid_0's binary_logloss: 0.69349\n",
      "[5]\tvalid_0's l1: 0.499319\tvalid_0's binary_logloss: 0.693893\n",
      "[6]\tvalid_0's l1: 0.498794\tvalid_0's binary_logloss: 0.693739\n",
      "[7]\tvalid_0's l1: 0.498049\tvalid_0's binary_logloss: 0.693254\n",
      "[8]\tvalid_0's l1: 0.497694\tvalid_0's binary_logloss: 0.693611\n",
      "Early stopping, best iteration is:\n",
      "[3]\tvalid_0's l1: 0.499091\tvalid_0's binary_logloss: 0.692253\n",
      "[1]\tvalid_0's l1: 0.50024\tvalid_0's binary_logloss: 0.694202\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.49866\tvalid_0's binary_logloss: 0.6916\n",
      "[3]\tvalid_0's l1: 0.497466\tvalid_0's binary_logloss: 0.690118\n",
      "[4]\tvalid_0's l1: 0.496775\tvalid_0's binary_logloss: 0.689527\n",
      "[5]\tvalid_0's l1: 0.496603\tvalid_0's binary_logloss: 0.690456\n",
      "[6]\tvalid_0's l1: 0.49607\tvalid_0's binary_logloss: 0.69082\n",
      "[7]\tvalid_0's l1: 0.495731\tvalid_0's binary_logloss: 0.691305\n",
      "[8]\tvalid_0's l1: 0.494276\tvalid_0's binary_logloss: 0.690151\n",
      "[9]\tvalid_0's l1: 0.49358\tvalid_0's binary_logloss: 0.690439\n",
      "Early stopping, best iteration is:\n",
      "[4]\tvalid_0's l1: 0.496775\tvalid_0's binary_logloss: 0.689527\n",
      "[1]\tvalid_0's l1: 0.500739\tvalid_0's binary_logloss: 0.695375\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500217\tvalid_0's binary_logloss: 0.694566\n",
      "[3]\tvalid_0's l1: 0.499029\tvalid_0's binary_logloss: 0.692881\n",
      "[4]\tvalid_0's l1: 0.498693\tvalid_0's binary_logloss: 0.692418\n",
      "[5]\tvalid_0's l1: 0.498086\tvalid_0's binary_logloss: 0.692412\n",
      "[6]\tvalid_0's l1: 0.497232\tvalid_0's binary_logloss: 0.691046\n",
      "[7]\tvalid_0's l1: 0.497169\tvalid_0's binary_logloss: 0.69228\n",
      "[8]\tvalid_0's l1: 0.495819\tvalid_0's binary_logloss: 0.690597\n",
      "[9]\tvalid_0's l1: 0.494719\tvalid_0's binary_logloss: 0.690008\n",
      "[10]\tvalid_0's l1: 0.494339\tvalid_0's binary_logloss: 0.690112\n",
      "[11]\tvalid_0's l1: 0.49345\tvalid_0's binary_logloss: 0.690136\n",
      "[12]\tvalid_0's l1: 0.493034\tvalid_0's binary_logloss: 0.690399\n",
      "[13]\tvalid_0's l1: 0.492896\tvalid_0's binary_logloss: 0.69148\n",
      "[14]\tvalid_0's l1: 0.492481\tvalid_0's binary_logloss: 0.691332\n",
      "Early stopping, best iteration is:\n",
      "[9]\tvalid_0's l1: 0.494719\tvalid_0's binary_logloss: 0.690008\n",
      "[1]\tvalid_0's l1: 0.499683\tvalid_0's binary_logloss: 0.693595\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.498137\tvalid_0's binary_logloss: 0.691269\n",
      "[3]\tvalid_0's l1: 0.496383\tvalid_0's binary_logloss: 0.688867\n",
      "[4]\tvalid_0's l1: 0.495584\tvalid_0's binary_logloss: 0.688003\n",
      "[5]\tvalid_0's l1: 0.494702\tvalid_0's binary_logloss: 0.687454\n",
      "[6]\tvalid_0's l1: 0.49428\tvalid_0's binary_logloss: 0.687657\n",
      "[7]\tvalid_0's l1: 0.493633\tvalid_0's binary_logloss: 0.687194\n",
      "[8]\tvalid_0's l1: 0.492774\tvalid_0's binary_logloss: 0.687367\n",
      "[9]\tvalid_0's l1: 0.492631\tvalid_0's binary_logloss: 0.688723\n",
      "[10]\tvalid_0's l1: 0.492344\tvalid_0's binary_logloss: 0.689085\n",
      "[11]\tvalid_0's l1: 0.491101\tvalid_0's binary_logloss: 0.688175\n",
      "[12]\tvalid_0's l1: 0.490473\tvalid_0's binary_logloss: 0.689075\n",
      "Early stopping, best iteration is:\n",
      "[7]\tvalid_0's l1: 0.493633\tvalid_0's binary_logloss: 0.687194\n",
      "[1]\tvalid_0's l1: 0.49998\tvalid_0's binary_logloss: 0.693805\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.497834\tvalid_0's binary_logloss: 0.689777\n",
      "[3]\tvalid_0's l1: 0.496964\tvalid_0's binary_logloss: 0.68825\n",
      "[4]\tvalid_0's l1: 0.495562\tvalid_0's binary_logloss: 0.686079\n",
      "[5]\tvalid_0's l1: 0.493892\tvalid_0's binary_logloss: 0.683593\n",
      "[6]\tvalid_0's l1: 0.493337\tvalid_0's binary_logloss: 0.683126\n",
      "[7]\tvalid_0's l1: 0.491981\tvalid_0's binary_logloss: 0.681505\n",
      "[8]\tvalid_0's l1: 0.49051\tvalid_0's binary_logloss: 0.678823\n",
      "[9]\tvalid_0's l1: 0.488975\tvalid_0's binary_logloss: 0.676579\n",
      "[10]\tvalid_0's l1: 0.489269\tvalid_0's binary_logloss: 0.677711\n",
      "[11]\tvalid_0's l1: 0.488243\tvalid_0's binary_logloss: 0.676685\n",
      "[12]\tvalid_0's l1: 0.488331\tvalid_0's binary_logloss: 0.677508\n",
      "[13]\tvalid_0's l1: 0.487504\tvalid_0's binary_logloss: 0.677646\n",
      "[14]\tvalid_0's l1: 0.487319\tvalid_0's binary_logloss: 0.67724\n",
      "Early stopping, best iteration is:\n",
      "[9]\tvalid_0's l1: 0.488975\tvalid_0's binary_logloss: 0.676579\n",
      "[1]\tvalid_0's l1: 0.500027\tvalid_0's binary_logloss: 0.693799\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.499582\tvalid_0's binary_logloss: 0.693072\n",
      "[3]\tvalid_0's l1: 0.499091\tvalid_0's binary_logloss: 0.692253\n",
      "[4]\tvalid_0's l1: 0.499462\tvalid_0's binary_logloss: 0.69349\n",
      "[5]\tvalid_0's l1: 0.499319\tvalid_0's binary_logloss: 0.693893\n",
      "[6]\tvalid_0's l1: 0.498794\tvalid_0's binary_logloss: 0.693739\n",
      "[7]\tvalid_0's l1: 0.498049\tvalid_0's binary_logloss: 0.693254\n",
      "[8]\tvalid_0's l1: 0.497694\tvalid_0's binary_logloss: 0.693611\n",
      "Early stopping, best iteration is:\n",
      "[3]\tvalid_0's l1: 0.499091\tvalid_0's binary_logloss: 0.692253\n",
      "[1]\tvalid_0's l1: 0.50024\tvalid_0's binary_logloss: 0.694202\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.49866\tvalid_0's binary_logloss: 0.6916\n",
      "[3]\tvalid_0's l1: 0.497466\tvalid_0's binary_logloss: 0.690118\n",
      "[4]\tvalid_0's l1: 0.496775\tvalid_0's binary_logloss: 0.689527\n",
      "[5]\tvalid_0's l1: 0.496603\tvalid_0's binary_logloss: 0.690456\n",
      "[6]\tvalid_0's l1: 0.49607\tvalid_0's binary_logloss: 0.69082\n",
      "[7]\tvalid_0's l1: 0.495731\tvalid_0's binary_logloss: 0.691305\n",
      "[8]\tvalid_0's l1: 0.494276\tvalid_0's binary_logloss: 0.690151\n",
      "[9]\tvalid_0's l1: 0.49358\tvalid_0's binary_logloss: 0.690439\n",
      "Early stopping, best iteration is:\n",
      "[4]\tvalid_0's l1: 0.496775\tvalid_0's binary_logloss: 0.689527\n",
      "[1]\tvalid_0's l1: 0.500739\tvalid_0's binary_logloss: 0.695374\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500217\tvalid_0's binary_logloss: 0.694564\n",
      "[3]\tvalid_0's l1: 0.499029\tvalid_0's binary_logloss: 0.692877\n",
      "[4]\tvalid_0's l1: 0.498692\tvalid_0's binary_logloss: 0.692415\n",
      "[5]\tvalid_0's l1: 0.498085\tvalid_0's binary_logloss: 0.692408\n",
      "[6]\tvalid_0's l1: 0.497231\tvalid_0's binary_logloss: 0.691042\n",
      "[7]\tvalid_0's l1: 0.497168\tvalid_0's binary_logloss: 0.692276\n",
      "[8]\tvalid_0's l1: 0.495817\tvalid_0's binary_logloss: 0.690593\n",
      "[9]\tvalid_0's l1: 0.494405\tvalid_0's binary_logloss: 0.689587\n",
      "[10]\tvalid_0's l1: 0.494029\tvalid_0's binary_logloss: 0.689746\n",
      "[11]\tvalid_0's l1: 0.493069\tvalid_0's binary_logloss: 0.689636\n",
      "[12]\tvalid_0's l1: 0.491902\tvalid_0's binary_logloss: 0.689261\n",
      "[13]\tvalid_0's l1: 0.491086\tvalid_0's binary_logloss: 0.688831\n",
      "[14]\tvalid_0's l1: 0.490831\tvalid_0's binary_logloss: 0.690531\n",
      "[15]\tvalid_0's l1: 0.490364\tvalid_0's binary_logloss: 0.690282\n",
      "[16]\tvalid_0's l1: 0.490603\tvalid_0's binary_logloss: 0.692082\n",
      "[17]\tvalid_0's l1: 0.490198\tvalid_0's binary_logloss: 0.693997\n",
      "[18]\tvalid_0's l1: 0.490106\tvalid_0's binary_logloss: 0.695334\n",
      "Early stopping, best iteration is:\n",
      "[13]\tvalid_0's l1: 0.491086\tvalid_0's binary_logloss: 0.688831\n",
      "[1]\tvalid_0's l1: 0.499797\tvalid_0's binary_logloss: 0.693815\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.498252\tvalid_0's binary_logloss: 0.691487\n",
      "[3]\tvalid_0's l1: 0.496713\tvalid_0's binary_logloss: 0.689454\n",
      "[4]\tvalid_0's l1: 0.495844\tvalid_0's binary_logloss: 0.688474\n",
      "[5]\tvalid_0's l1: 0.495091\tvalid_0's binary_logloss: 0.688216\n",
      "[6]\tvalid_0's l1: 0.494663\tvalid_0's binary_logloss: 0.688387\n",
      "[7]\tvalid_0's l1: 0.494013\tvalid_0's binary_logloss: 0.687874\n",
      "[8]\tvalid_0's l1: 0.493153\tvalid_0's binary_logloss: 0.688006\n",
      "[9]\tvalid_0's l1: 0.493005\tvalid_0's binary_logloss: 0.689338\n",
      "[10]\tvalid_0's l1: 0.492912\tvalid_0's binary_logloss: 0.690043\n",
      "[11]\tvalid_0's l1: 0.491543\tvalid_0's binary_logloss: 0.688962\n",
      "[12]\tvalid_0's l1: 0.490459\tvalid_0's binary_logloss: 0.688999\n",
      "Early stopping, best iteration is:\n",
      "[7]\tvalid_0's l1: 0.494013\tvalid_0's binary_logloss: 0.687874\n",
      "[1]\tvalid_0's l1: 0.49998\tvalid_0's binary_logloss: 0.693805\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.498115\tvalid_0's binary_logloss: 0.690297\n",
      "[3]\tvalid_0's l1: 0.497681\tvalid_0's binary_logloss: 0.689521\n",
      "[4]\tvalid_0's l1: 0.49633\tvalid_0's binary_logloss: 0.687592\n",
      "[5]\tvalid_0's l1: 0.495405\tvalid_0's binary_logloss: 0.686081\n",
      "[6]\tvalid_0's l1: 0.494077\tvalid_0's binary_logloss: 0.684603\n",
      "[7]\tvalid_0's l1: 0.493777\tvalid_0's binary_logloss: 0.685006\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[8]\tvalid_0's l1: 0.493028\tvalid_0's binary_logloss: 0.68427\n",
      "[9]\tvalid_0's l1: 0.492093\tvalid_0's binary_logloss: 0.68256\n",
      "[10]\tvalid_0's l1: 0.490633\tvalid_0's binary_logloss: 0.68097\n",
      "[11]\tvalid_0's l1: 0.48917\tvalid_0's binary_logloss: 0.678713\n",
      "[12]\tvalid_0's l1: 0.488272\tvalid_0's binary_logloss: 0.677289\n",
      "[13]\tvalid_0's l1: 0.487393\tvalid_0's binary_logloss: 0.675807\n",
      "[14]\tvalid_0's l1: 0.486343\tvalid_0's binary_logloss: 0.674324\n",
      "[15]\tvalid_0's l1: 0.485867\tvalid_0's binary_logloss: 0.673972\n",
      "[16]\tvalid_0's l1: 0.485703\tvalid_0's binary_logloss: 0.67394\n",
      "[17]\tvalid_0's l1: 0.484869\tvalid_0's binary_logloss: 0.673044\n",
      "[18]\tvalid_0's l1: 0.483842\tvalid_0's binary_logloss: 0.672492\n",
      "[19]\tvalid_0's l1: 0.48355\tvalid_0's binary_logloss: 0.672442\n",
      "[20]\tvalid_0's l1: 0.482171\tvalid_0's binary_logloss: 0.67043\n",
      "[21]\tvalid_0's l1: 0.48214\tvalid_0's binary_logloss: 0.671283\n",
      "[22]\tvalid_0's l1: 0.481526\tvalid_0's binary_logloss: 0.670743\n",
      "[23]\tvalid_0's l1: 0.480885\tvalid_0's binary_logloss: 0.670321\n",
      "[24]\tvalid_0's l1: 0.479818\tvalid_0's binary_logloss: 0.669276\n",
      "[25]\tvalid_0's l1: 0.479672\tvalid_0's binary_logloss: 0.670102\n",
      "[26]\tvalid_0's l1: 0.478814\tvalid_0's binary_logloss: 0.669603\n",
      "[27]\tvalid_0's l1: 0.477851\tvalid_0's binary_logloss: 0.668546\n",
      "[28]\tvalid_0's l1: 0.477276\tvalid_0's binary_logloss: 0.667566\n",
      "[29]\tvalid_0's l1: 0.476935\tvalid_0's binary_logloss: 0.667372\n",
      "[30]\tvalid_0's l1: 0.476828\tvalid_0's binary_logloss: 0.668177\n",
      "[31]\tvalid_0's l1: 0.476465\tvalid_0's binary_logloss: 0.667519\n",
      "[32]\tvalid_0's l1: 0.475634\tvalid_0's binary_logloss: 0.666702\n",
      "[33]\tvalid_0's l1: 0.475327\tvalid_0's binary_logloss: 0.667471\n",
      "[34]\tvalid_0's l1: 0.474578\tvalid_0's binary_logloss: 0.666829\n",
      "[35]\tvalid_0's l1: 0.474819\tvalid_0's binary_logloss: 0.667748\n",
      "[36]\tvalid_0's l1: 0.474034\tvalid_0's binary_logloss: 0.666847\n",
      "[37]\tvalid_0's l1: 0.473523\tvalid_0's binary_logloss: 0.666575\n",
      "[38]\tvalid_0's l1: 0.473162\tvalid_0's binary_logloss: 0.66675\n",
      "[39]\tvalid_0's l1: 0.472691\tvalid_0's binary_logloss: 0.66603\n",
      "[40]\tvalid_0's l1: 0.472217\tvalid_0's binary_logloss: 0.665692\n",
      "[41]\tvalid_0's l1: 0.471943\tvalid_0's binary_logloss: 0.666622\n",
      "[42]\tvalid_0's l1: 0.471648\tvalid_0's binary_logloss: 0.665957\n",
      "[43]\tvalid_0's l1: 0.471382\tvalid_0's binary_logloss: 0.665157\n",
      "[44]\tvalid_0's l1: 0.471733\tvalid_0's binary_logloss: 0.666714\n",
      "[45]\tvalid_0's l1: 0.471541\tvalid_0's binary_logloss: 0.666641\n",
      "[46]\tvalid_0's l1: 0.471832\tvalid_0's binary_logloss: 0.666781\n",
      "[47]\tvalid_0's l1: 0.47139\tvalid_0's binary_logloss: 0.666713\n",
      "[48]\tvalid_0's l1: 0.470897\tvalid_0's binary_logloss: 0.665888\n",
      "Early stopping, best iteration is:\n",
      "[43]\tvalid_0's l1: 0.471382\tvalid_0's binary_logloss: 0.665157\n",
      "[1]\tvalid_0's l1: 0.500027\tvalid_0's binary_logloss: 0.693799\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.499582\tvalid_0's binary_logloss: 0.693072\n",
      "[3]\tvalid_0's l1: 0.499108\tvalid_0's binary_logloss: 0.692256\n",
      "[4]\tvalid_0's l1: 0.499481\tvalid_0's binary_logloss: 0.693495\n",
      "[5]\tvalid_0's l1: 0.499418\tvalid_0's binary_logloss: 0.694043\n",
      "[6]\tvalid_0's l1: 0.498864\tvalid_0's binary_logloss: 0.69381\n",
      "[7]\tvalid_0's l1: 0.498548\tvalid_0's binary_logloss: 0.694357\n",
      "[8]\tvalid_0's l1: 0.497925\tvalid_0's binary_logloss: 0.694231\n",
      "Early stopping, best iteration is:\n",
      "[3]\tvalid_0's l1: 0.499108\tvalid_0's binary_logloss: 0.692256\n",
      "[1]\tvalid_0's l1: 0.50024\tvalid_0's binary_logloss: 0.694202\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.49866\tvalid_0's binary_logloss: 0.6916\n",
      "[3]\tvalid_0's l1: 0.497466\tvalid_0's binary_logloss: 0.690118\n",
      "[4]\tvalid_0's l1: 0.496775\tvalid_0's binary_logloss: 0.689527\n",
      "[5]\tvalid_0's l1: 0.496603\tvalid_0's binary_logloss: 0.690456\n",
      "[6]\tvalid_0's l1: 0.49607\tvalid_0's binary_logloss: 0.69082\n",
      "[7]\tvalid_0's l1: 0.495731\tvalid_0's binary_logloss: 0.691306\n",
      "[8]\tvalid_0's l1: 0.494276\tvalid_0's binary_logloss: 0.690151\n",
      "[9]\tvalid_0's l1: 0.493837\tvalid_0's binary_logloss: 0.690852\n",
      "Early stopping, best iteration is:\n",
      "[4]\tvalid_0's l1: 0.496775\tvalid_0's binary_logloss: 0.689527\n",
      "[1]\tvalid_0's l1: 0.500739\tvalid_0's binary_logloss: 0.695375\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500217\tvalid_0's binary_logloss: 0.694566\n",
      "[3]\tvalid_0's l1: 0.499029\tvalid_0's binary_logloss: 0.692881\n",
      "[4]\tvalid_0's l1: 0.498693\tvalid_0's binary_logloss: 0.692418\n",
      "[5]\tvalid_0's l1: 0.498086\tvalid_0's binary_logloss: 0.692412\n",
      "[6]\tvalid_0's l1: 0.497232\tvalid_0's binary_logloss: 0.691046\n",
      "[7]\tvalid_0's l1: 0.497169\tvalid_0's binary_logloss: 0.69228\n",
      "[8]\tvalid_0's l1: 0.495819\tvalid_0's binary_logloss: 0.690597\n",
      "[9]\tvalid_0's l1: 0.494719\tvalid_0's binary_logloss: 0.690008\n",
      "[10]\tvalid_0's l1: 0.494339\tvalid_0's binary_logloss: 0.690112\n",
      "[11]\tvalid_0's l1: 0.49345\tvalid_0's binary_logloss: 0.690136\n",
      "[12]\tvalid_0's l1: 0.493034\tvalid_0's binary_logloss: 0.690399\n",
      "[13]\tvalid_0's l1: 0.492896\tvalid_0's binary_logloss: 0.69148\n",
      "[14]\tvalid_0's l1: 0.492481\tvalid_0's binary_logloss: 0.691332\n",
      "Early stopping, best iteration is:\n",
      "[9]\tvalid_0's l1: 0.494719\tvalid_0's binary_logloss: 0.690008\n",
      "[1]\tvalid_0's l1: 0.499683\tvalid_0's binary_logloss: 0.693595\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.498137\tvalid_0's binary_logloss: 0.691269\n",
      "[3]\tvalid_0's l1: 0.496383\tvalid_0's binary_logloss: 0.688867\n",
      "[4]\tvalid_0's l1: 0.495584\tvalid_0's binary_logloss: 0.688003\n",
      "[5]\tvalid_0's l1: 0.494702\tvalid_0's binary_logloss: 0.687454\n",
      "[6]\tvalid_0's l1: 0.49428\tvalid_0's binary_logloss: 0.687657\n",
      "[7]\tvalid_0's l1: 0.493633\tvalid_0's binary_logloss: 0.687194\n",
      "[8]\tvalid_0's l1: 0.492774\tvalid_0's binary_logloss: 0.687367\n",
      "[9]\tvalid_0's l1: 0.492631\tvalid_0's binary_logloss: 0.688723\n",
      "[10]\tvalid_0's l1: 0.492344\tvalid_0's binary_logloss: 0.689085\n",
      "[11]\tvalid_0's l1: 0.491101\tvalid_0's binary_logloss: 0.688175\n",
      "[12]\tvalid_0's l1: 0.490473\tvalid_0's binary_logloss: 0.689075\n",
      "Early stopping, best iteration is:\n",
      "[7]\tvalid_0's l1: 0.493633\tvalid_0's binary_logloss: 0.687194\n",
      "[1]\tvalid_0's l1: 0.49998\tvalid_0's binary_logloss: 0.693805\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.497834\tvalid_0's binary_logloss: 0.689777\n",
      "[3]\tvalid_0's l1: 0.496964\tvalid_0's binary_logloss: 0.68825\n",
      "[4]\tvalid_0's l1: 0.495562\tvalid_0's binary_logloss: 0.686079\n",
      "[5]\tvalid_0's l1: 0.493892\tvalid_0's binary_logloss: 0.683593\n",
      "[6]\tvalid_0's l1: 0.493337\tvalid_0's binary_logloss: 0.683126\n",
      "[7]\tvalid_0's l1: 0.491981\tvalid_0's binary_logloss: 0.681505\n",
      "[8]\tvalid_0's l1: 0.49051\tvalid_0's binary_logloss: 0.678823\n",
      "[9]\tvalid_0's l1: 0.488975\tvalid_0's binary_logloss: 0.676579\n",
      "[10]\tvalid_0's l1: 0.489269\tvalid_0's binary_logloss: 0.677711\n",
      "[11]\tvalid_0's l1: 0.488243\tvalid_0's binary_logloss: 0.676685\n",
      "[12]\tvalid_0's l1: 0.488331\tvalid_0's binary_logloss: 0.677508\n",
      "[13]\tvalid_0's l1: 0.487504\tvalid_0's binary_logloss: 0.677646\n",
      "[14]\tvalid_0's l1: 0.487319\tvalid_0's binary_logloss: 0.67724\n",
      "Early stopping, best iteration is:\n",
      "[9]\tvalid_0's l1: 0.488975\tvalid_0's binary_logloss: 0.676579\n",
      "[1]\tvalid_0's l1: 0.500027\tvalid_0's binary_logloss: 0.693799\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.499582\tvalid_0's binary_logloss: 0.693072\n",
      "[3]\tvalid_0's l1: 0.499091\tvalid_0's binary_logloss: 0.692253\n",
      "[4]\tvalid_0's l1: 0.499462\tvalid_0's binary_logloss: 0.69349\n",
      "[5]\tvalid_0's l1: 0.499319\tvalid_0's binary_logloss: 0.693893\n",
      "[6]\tvalid_0's l1: 0.498794\tvalid_0's binary_logloss: 0.693739\n",
      "[7]\tvalid_0's l1: 0.498049\tvalid_0's binary_logloss: 0.693254\n",
      "[8]\tvalid_0's l1: 0.497694\tvalid_0's binary_logloss: 0.693611\n",
      "Early stopping, best iteration is:\n",
      "[3]\tvalid_0's l1: 0.499091\tvalid_0's binary_logloss: 0.692253\n",
      "[1]\tvalid_0's l1: 0.50024\tvalid_0's binary_logloss: 0.694202\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.49866\tvalid_0's binary_logloss: 0.6916\n",
      "[3]\tvalid_0's l1: 0.497466\tvalid_0's binary_logloss: 0.690118\n",
      "[4]\tvalid_0's l1: 0.496775\tvalid_0's binary_logloss: 0.689527\n",
      "[5]\tvalid_0's l1: 0.496603\tvalid_0's binary_logloss: 0.690456\n",
      "[6]\tvalid_0's l1: 0.49607\tvalid_0's binary_logloss: 0.69082\n",
      "[7]\tvalid_0's l1: 0.495731\tvalid_0's binary_logloss: 0.691305\n",
      "[8]\tvalid_0's l1: 0.494276\tvalid_0's binary_logloss: 0.690151\n",
      "[9]\tvalid_0's l1: 0.49358\tvalid_0's binary_logloss: 0.690439\n",
      "Early stopping, best iteration is:\n",
      "[4]\tvalid_0's l1: 0.496775\tvalid_0's binary_logloss: 0.689527\n",
      "[1]\tvalid_0's l1: 0.500739\tvalid_0's binary_logloss: 0.695375\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500217\tvalid_0's binary_logloss: 0.694566\n",
      "[3]\tvalid_0's l1: 0.499029\tvalid_0's binary_logloss: 0.692881\n",
      "[4]\tvalid_0's l1: 0.498693\tvalid_0's binary_logloss: 0.692418\n",
      "[5]\tvalid_0's l1: 0.498086\tvalid_0's binary_logloss: 0.692412\n",
      "[6]\tvalid_0's l1: 0.497232\tvalid_0's binary_logloss: 0.691046\n",
      "[7]\tvalid_0's l1: 0.497169\tvalid_0's binary_logloss: 0.69228\n",
      "[8]\tvalid_0's l1: 0.495819\tvalid_0's binary_logloss: 0.690597\n",
      "[9]\tvalid_0's l1: 0.494719\tvalid_0's binary_logloss: 0.690008\n",
      "[10]\tvalid_0's l1: 0.494339\tvalid_0's binary_logloss: 0.690112\n",
      "[11]\tvalid_0's l1: 0.49345\tvalid_0's binary_logloss: 0.690136\n",
      "[12]\tvalid_0's l1: 0.493034\tvalid_0's binary_logloss: 0.690399\n",
      "[13]\tvalid_0's l1: 0.492896\tvalid_0's binary_logloss: 0.69148\n",
      "[14]\tvalid_0's l1: 0.492481\tvalid_0's binary_logloss: 0.691332\n",
      "Early stopping, best iteration is:\n",
      "[9]\tvalid_0's l1: 0.494719\tvalid_0's binary_logloss: 0.690008\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1]\tvalid_0's l1: 0.499683\tvalid_0's binary_logloss: 0.693595\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.498137\tvalid_0's binary_logloss: 0.691269\n",
      "[3]\tvalid_0's l1: 0.496383\tvalid_0's binary_logloss: 0.688867\n",
      "[4]\tvalid_0's l1: 0.495584\tvalid_0's binary_logloss: 0.688003\n",
      "[5]\tvalid_0's l1: 0.494702\tvalid_0's binary_logloss: 0.687454\n",
      "[6]\tvalid_0's l1: 0.49428\tvalid_0's binary_logloss: 0.687657\n",
      "[7]\tvalid_0's l1: 0.493633\tvalid_0's binary_logloss: 0.687194\n",
      "[8]\tvalid_0's l1: 0.492774\tvalid_0's binary_logloss: 0.687367\n",
      "[9]\tvalid_0's l1: 0.492631\tvalid_0's binary_logloss: 0.688723\n",
      "[10]\tvalid_0's l1: 0.492344\tvalid_0's binary_logloss: 0.689085\n",
      "[11]\tvalid_0's l1: 0.491101\tvalid_0's binary_logloss: 0.688175\n",
      "[12]\tvalid_0's l1: 0.490473\tvalid_0's binary_logloss: 0.689075\n",
      "Early stopping, best iteration is:\n",
      "[7]\tvalid_0's l1: 0.493633\tvalid_0's binary_logloss: 0.687194\n",
      "[1]\tvalid_0's l1: 0.49998\tvalid_0's binary_logloss: 0.693805\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.497834\tvalid_0's binary_logloss: 0.689777\n",
      "[3]\tvalid_0's l1: 0.496964\tvalid_0's binary_logloss: 0.68825\n",
      "[4]\tvalid_0's l1: 0.495562\tvalid_0's binary_logloss: 0.686079\n",
      "[5]\tvalid_0's l1: 0.493892\tvalid_0's binary_logloss: 0.683593\n",
      "[6]\tvalid_0's l1: 0.493337\tvalid_0's binary_logloss: 0.683126\n",
      "[7]\tvalid_0's l1: 0.491981\tvalid_0's binary_logloss: 0.681505\n",
      "[8]\tvalid_0's l1: 0.49051\tvalid_0's binary_logloss: 0.678823\n",
      "[9]\tvalid_0's l1: 0.488975\tvalid_0's binary_logloss: 0.676579\n",
      "[10]\tvalid_0's l1: 0.489269\tvalid_0's binary_logloss: 0.677711\n",
      "[11]\tvalid_0's l1: 0.488243\tvalid_0's binary_logloss: 0.676685\n",
      "[12]\tvalid_0's l1: 0.488331\tvalid_0's binary_logloss: 0.677508\n",
      "[13]\tvalid_0's l1: 0.487504\tvalid_0's binary_logloss: 0.677646\n",
      "[14]\tvalid_0's l1: 0.487319\tvalid_0's binary_logloss: 0.67724\n",
      "Early stopping, best iteration is:\n",
      "[9]\tvalid_0's l1: 0.488975\tvalid_0's binary_logloss: 0.676579\n",
      "[1]\tvalid_0's l1: 0.500027\tvalid_0's binary_logloss: 0.693799\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.499582\tvalid_0's binary_logloss: 0.693072\n",
      "[3]\tvalid_0's l1: 0.499091\tvalid_0's binary_logloss: 0.692253\n",
      "[4]\tvalid_0's l1: 0.499462\tvalid_0's binary_logloss: 0.69349\n",
      "[5]\tvalid_0's l1: 0.499319\tvalid_0's binary_logloss: 0.693893\n",
      "[6]\tvalid_0's l1: 0.498794\tvalid_0's binary_logloss: 0.693739\n",
      "[7]\tvalid_0's l1: 0.498049\tvalid_0's binary_logloss: 0.693254\n",
      "[8]\tvalid_0's l1: 0.497694\tvalid_0's binary_logloss: 0.693611\n",
      "Early stopping, best iteration is:\n",
      "[3]\tvalid_0's l1: 0.499091\tvalid_0's binary_logloss: 0.692253\n",
      "[1]\tvalid_0's l1: 0.50024\tvalid_0's binary_logloss: 0.694202\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.49866\tvalid_0's binary_logloss: 0.6916\n",
      "[3]\tvalid_0's l1: 0.497466\tvalid_0's binary_logloss: 0.690118\n",
      "[4]\tvalid_0's l1: 0.496775\tvalid_0's binary_logloss: 0.689527\n",
      "[5]\tvalid_0's l1: 0.496603\tvalid_0's binary_logloss: 0.690456\n",
      "[6]\tvalid_0's l1: 0.49607\tvalid_0's binary_logloss: 0.69082\n",
      "[7]\tvalid_0's l1: 0.495731\tvalid_0's binary_logloss: 0.691305\n",
      "[8]\tvalid_0's l1: 0.494276\tvalid_0's binary_logloss: 0.690151\n",
      "[9]\tvalid_0's l1: 0.49358\tvalid_0's binary_logloss: 0.690439\n",
      "Early stopping, best iteration is:\n",
      "[4]\tvalid_0's l1: 0.496775\tvalid_0's binary_logloss: 0.689527\n",
      "[1]\tvalid_0's l1: 0.500739\tvalid_0's binary_logloss: 0.695374\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500217\tvalid_0's binary_logloss: 0.694564\n",
      "[3]\tvalid_0's l1: 0.499029\tvalid_0's binary_logloss: 0.692877\n",
      "[4]\tvalid_0's l1: 0.498692\tvalid_0's binary_logloss: 0.692415\n",
      "[5]\tvalid_0's l1: 0.498085\tvalid_0's binary_logloss: 0.692408\n",
      "[6]\tvalid_0's l1: 0.497231\tvalid_0's binary_logloss: 0.691042\n",
      "[7]\tvalid_0's l1: 0.497168\tvalid_0's binary_logloss: 0.692276\n",
      "[8]\tvalid_0's l1: 0.495817\tvalid_0's binary_logloss: 0.690593\n",
      "[9]\tvalid_0's l1: 0.494405\tvalid_0's binary_logloss: 0.689587\n",
      "[10]\tvalid_0's l1: 0.494029\tvalid_0's binary_logloss: 0.689746\n",
      "[11]\tvalid_0's l1: 0.493069\tvalid_0's binary_logloss: 0.689636\n",
      "[12]\tvalid_0's l1: 0.491902\tvalid_0's binary_logloss: 0.689261\n",
      "[13]\tvalid_0's l1: 0.491086\tvalid_0's binary_logloss: 0.688831\n",
      "[14]\tvalid_0's l1: 0.490831\tvalid_0's binary_logloss: 0.690531\n",
      "[15]\tvalid_0's l1: 0.490364\tvalid_0's binary_logloss: 0.690282\n",
      "[16]\tvalid_0's l1: 0.490603\tvalid_0's binary_logloss: 0.692082\n",
      "[17]\tvalid_0's l1: 0.490198\tvalid_0's binary_logloss: 0.693997\n",
      "[18]\tvalid_0's l1: 0.490106\tvalid_0's binary_logloss: 0.695334\n",
      "Early stopping, best iteration is:\n",
      "[13]\tvalid_0's l1: 0.491086\tvalid_0's binary_logloss: 0.688831\n",
      "[1]\tvalid_0's l1: 0.499797\tvalid_0's binary_logloss: 0.693815\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.498252\tvalid_0's binary_logloss: 0.691487\n",
      "[3]\tvalid_0's l1: 0.496713\tvalid_0's binary_logloss: 0.689454\n",
      "[4]\tvalid_0's l1: 0.495844\tvalid_0's binary_logloss: 0.688474\n",
      "[5]\tvalid_0's l1: 0.495091\tvalid_0's binary_logloss: 0.688216\n",
      "[6]\tvalid_0's l1: 0.494663\tvalid_0's binary_logloss: 0.688387\n",
      "[7]\tvalid_0's l1: 0.494013\tvalid_0's binary_logloss: 0.687874\n",
      "[8]\tvalid_0's l1: 0.493153\tvalid_0's binary_logloss: 0.688006\n",
      "[9]\tvalid_0's l1: 0.493005\tvalid_0's binary_logloss: 0.689338\n",
      "[10]\tvalid_0's l1: 0.492912\tvalid_0's binary_logloss: 0.690043\n",
      "[11]\tvalid_0's l1: 0.491543\tvalid_0's binary_logloss: 0.688962\n",
      "[12]\tvalid_0's l1: 0.490459\tvalid_0's binary_logloss: 0.688999\n",
      "Early stopping, best iteration is:\n",
      "[7]\tvalid_0's l1: 0.494013\tvalid_0's binary_logloss: 0.687874\n",
      "[1]\tvalid_0's l1: 0.49998\tvalid_0's binary_logloss: 0.693805\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.498115\tvalid_0's binary_logloss: 0.690297\n",
      "[3]\tvalid_0's l1: 0.497681\tvalid_0's binary_logloss: 0.689521\n",
      "[4]\tvalid_0's l1: 0.49633\tvalid_0's binary_logloss: 0.687592\n",
      "[5]\tvalid_0's l1: 0.495405\tvalid_0's binary_logloss: 0.686081\n",
      "[6]\tvalid_0's l1: 0.494077\tvalid_0's binary_logloss: 0.684603\n",
      "[7]\tvalid_0's l1: 0.493777\tvalid_0's binary_logloss: 0.685006\n",
      "[8]\tvalid_0's l1: 0.493028\tvalid_0's binary_logloss: 0.68427\n",
      "[9]\tvalid_0's l1: 0.492093\tvalid_0's binary_logloss: 0.68256\n",
      "[10]\tvalid_0's l1: 0.490633\tvalid_0's binary_logloss: 0.68097\n",
      "[11]\tvalid_0's l1: 0.48917\tvalid_0's binary_logloss: 0.678713\n",
      "[12]\tvalid_0's l1: 0.488272\tvalid_0's binary_logloss: 0.677289\n",
      "[13]\tvalid_0's l1: 0.487393\tvalid_0's binary_logloss: 0.675807\n",
      "[14]\tvalid_0's l1: 0.486343\tvalid_0's binary_logloss: 0.674324\n",
      "[15]\tvalid_0's l1: 0.485867\tvalid_0's binary_logloss: 0.673972\n",
      "[16]\tvalid_0's l1: 0.485703\tvalid_0's binary_logloss: 0.67394\n",
      "[17]\tvalid_0's l1: 0.484869\tvalid_0's binary_logloss: 0.673044\n",
      "[18]\tvalid_0's l1: 0.483842\tvalid_0's binary_logloss: 0.672492\n",
      "[19]\tvalid_0's l1: 0.48355\tvalid_0's binary_logloss: 0.672442\n",
      "[20]\tvalid_0's l1: 0.482171\tvalid_0's binary_logloss: 0.67043\n",
      "[21]\tvalid_0's l1: 0.48214\tvalid_0's binary_logloss: 0.671283\n",
      "[22]\tvalid_0's l1: 0.481526\tvalid_0's binary_logloss: 0.670743\n",
      "[23]\tvalid_0's l1: 0.480885\tvalid_0's binary_logloss: 0.670321\n",
      "[24]\tvalid_0's l1: 0.479818\tvalid_0's binary_logloss: 0.669276\n",
      "[25]\tvalid_0's l1: 0.479672\tvalid_0's binary_logloss: 0.670102\n",
      "[26]\tvalid_0's l1: 0.478814\tvalid_0's binary_logloss: 0.669603\n",
      "[27]\tvalid_0's l1: 0.477851\tvalid_0's binary_logloss: 0.668546\n",
      "[28]\tvalid_0's l1: 0.477276\tvalid_0's binary_logloss: 0.667566\n",
      "[29]\tvalid_0's l1: 0.476935\tvalid_0's binary_logloss: 0.667372\n",
      "[30]\tvalid_0's l1: 0.476828\tvalid_0's binary_logloss: 0.668177\n",
      "[31]\tvalid_0's l1: 0.476465\tvalid_0's binary_logloss: 0.667519\n",
      "[32]\tvalid_0's l1: 0.475634\tvalid_0's binary_logloss: 0.666702\n",
      "[33]\tvalid_0's l1: 0.475327\tvalid_0's binary_logloss: 0.667471\n",
      "[34]\tvalid_0's l1: 0.474578\tvalid_0's binary_logloss: 0.666829\n",
      "[35]\tvalid_0's l1: 0.474819\tvalid_0's binary_logloss: 0.667748\n",
      "[36]\tvalid_0's l1: 0.474034\tvalid_0's binary_logloss: 0.666847\n",
      "[37]\tvalid_0's l1: 0.473523\tvalid_0's binary_logloss: 0.666575\n",
      "[38]\tvalid_0's l1: 0.473162\tvalid_0's binary_logloss: 0.66675\n",
      "[39]\tvalid_0's l1: 0.472691\tvalid_0's binary_logloss: 0.66603\n",
      "[40]\tvalid_0's l1: 0.472217\tvalid_0's binary_logloss: 0.665692\n",
      "[41]\tvalid_0's l1: 0.471943\tvalid_0's binary_logloss: 0.666622\n",
      "[42]\tvalid_0's l1: 0.471648\tvalid_0's binary_logloss: 0.665957\n",
      "[43]\tvalid_0's l1: 0.471382\tvalid_0's binary_logloss: 0.665157\n",
      "[44]\tvalid_0's l1: 0.471733\tvalid_0's binary_logloss: 0.666714\n",
      "[45]\tvalid_0's l1: 0.471541\tvalid_0's binary_logloss: 0.666641\n",
      "[46]\tvalid_0's l1: 0.471832\tvalid_0's binary_logloss: 0.666781\n",
      "[47]\tvalid_0's l1: 0.47139\tvalid_0's binary_logloss: 0.666713\n",
      "[48]\tvalid_0's l1: 0.470897\tvalid_0's binary_logloss: 0.665888\n",
      "Early stopping, best iteration is:\n",
      "[43]\tvalid_0's l1: 0.471382\tvalid_0's binary_logloss: 0.665157\n",
      "[1]\tvalid_0's l1: 0.500027\tvalid_0's binary_logloss: 0.693799\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.499582\tvalid_0's binary_logloss: 0.693072\n",
      "[3]\tvalid_0's l1: 0.499108\tvalid_0's binary_logloss: 0.692256\n",
      "[4]\tvalid_0's l1: 0.499481\tvalid_0's binary_logloss: 0.693495\n",
      "[5]\tvalid_0's l1: 0.499418\tvalid_0's binary_logloss: 0.694043\n",
      "[6]\tvalid_0's l1: 0.498864\tvalid_0's binary_logloss: 0.69381\n",
      "[7]\tvalid_0's l1: 0.498548\tvalid_0's binary_logloss: 0.694357\n",
      "[8]\tvalid_0's l1: 0.497925\tvalid_0's binary_logloss: 0.694231\n",
      "Early stopping, best iteration is:\n",
      "[3]\tvalid_0's l1: 0.499108\tvalid_0's binary_logloss: 0.692256\n",
      "[1]\tvalid_0's l1: 0.50024\tvalid_0's binary_logloss: 0.694202\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.49866\tvalid_0's binary_logloss: 0.6916\n",
      "[3]\tvalid_0's l1: 0.497466\tvalid_0's binary_logloss: 0.690118\n",
      "[4]\tvalid_0's l1: 0.496775\tvalid_0's binary_logloss: 0.689527\n",
      "[5]\tvalid_0's l1: 0.496603\tvalid_0's binary_logloss: 0.690456\n",
      "[6]\tvalid_0's l1: 0.49607\tvalid_0's binary_logloss: 0.69082\n",
      "[7]\tvalid_0's l1: 0.495731\tvalid_0's binary_logloss: 0.691306\n",
      "[8]\tvalid_0's l1: 0.494276\tvalid_0's binary_logloss: 0.690151\n",
      "[9]\tvalid_0's l1: 0.493837\tvalid_0's binary_logloss: 0.690852\n",
      "Early stopping, best iteration is:\n",
      "[4]\tvalid_0's l1: 0.496775\tvalid_0's binary_logloss: 0.689527\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1]\tvalid_0's l1: 0.500739\tvalid_0's binary_logloss: 0.695375\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500217\tvalid_0's binary_logloss: 0.694566\n",
      "[3]\tvalid_0's l1: 0.499029\tvalid_0's binary_logloss: 0.692881\n",
      "[4]\tvalid_0's l1: 0.498693\tvalid_0's binary_logloss: 0.692418\n",
      "[5]\tvalid_0's l1: 0.498086\tvalid_0's binary_logloss: 0.692412\n",
      "[6]\tvalid_0's l1: 0.497232\tvalid_0's binary_logloss: 0.691046\n",
      "[7]\tvalid_0's l1: 0.497169\tvalid_0's binary_logloss: 0.69228\n",
      "[8]\tvalid_0's l1: 0.495819\tvalid_0's binary_logloss: 0.690597\n",
      "[9]\tvalid_0's l1: 0.494719\tvalid_0's binary_logloss: 0.690008\n",
      "[10]\tvalid_0's l1: 0.494339\tvalid_0's binary_logloss: 0.690112\n",
      "[11]\tvalid_0's l1: 0.49345\tvalid_0's binary_logloss: 0.690136\n",
      "[12]\tvalid_0's l1: 0.493034\tvalid_0's binary_logloss: 0.690399\n",
      "[13]\tvalid_0's l1: 0.492896\tvalid_0's binary_logloss: 0.69148\n",
      "[14]\tvalid_0's l1: 0.492481\tvalid_0's binary_logloss: 0.691332\n",
      "Early stopping, best iteration is:\n",
      "[9]\tvalid_0's l1: 0.494719\tvalid_0's binary_logloss: 0.690008\n",
      "[1]\tvalid_0's l1: 0.499683\tvalid_0's binary_logloss: 0.693595\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.498137\tvalid_0's binary_logloss: 0.691269\n",
      "[3]\tvalid_0's l1: 0.496383\tvalid_0's binary_logloss: 0.688867\n",
      "[4]\tvalid_0's l1: 0.495584\tvalid_0's binary_logloss: 0.688003\n",
      "[5]\tvalid_0's l1: 0.494702\tvalid_0's binary_logloss: 0.687454\n",
      "[6]\tvalid_0's l1: 0.49428\tvalid_0's binary_logloss: 0.687657\n",
      "[7]\tvalid_0's l1: 0.493633\tvalid_0's binary_logloss: 0.687194\n",
      "[8]\tvalid_0's l1: 0.492774\tvalid_0's binary_logloss: 0.687367\n",
      "[9]\tvalid_0's l1: 0.492631\tvalid_0's binary_logloss: 0.688723\n",
      "[10]\tvalid_0's l1: 0.492344\tvalid_0's binary_logloss: 0.689085\n",
      "[11]\tvalid_0's l1: 0.491101\tvalid_0's binary_logloss: 0.688175\n",
      "[12]\tvalid_0's l1: 0.490473\tvalid_0's binary_logloss: 0.689075\n",
      "Early stopping, best iteration is:\n",
      "[7]\tvalid_0's l1: 0.493633\tvalid_0's binary_logloss: 0.687194\n",
      "[1]\tvalid_0's l1: 0.49998\tvalid_0's binary_logloss: 0.693805\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.497834\tvalid_0's binary_logloss: 0.689777\n",
      "[3]\tvalid_0's l1: 0.496964\tvalid_0's binary_logloss: 0.68825\n",
      "[4]\tvalid_0's l1: 0.495562\tvalid_0's binary_logloss: 0.686079\n",
      "[5]\tvalid_0's l1: 0.493892\tvalid_0's binary_logloss: 0.683593\n",
      "[6]\tvalid_0's l1: 0.493337\tvalid_0's binary_logloss: 0.683126\n",
      "[7]\tvalid_0's l1: 0.491981\tvalid_0's binary_logloss: 0.681505\n",
      "[8]\tvalid_0's l1: 0.49051\tvalid_0's binary_logloss: 0.678823\n",
      "[9]\tvalid_0's l1: 0.488975\tvalid_0's binary_logloss: 0.676579\n",
      "[10]\tvalid_0's l1: 0.489269\tvalid_0's binary_logloss: 0.677711\n",
      "[11]\tvalid_0's l1: 0.488243\tvalid_0's binary_logloss: 0.676685\n",
      "[12]\tvalid_0's l1: 0.488331\tvalid_0's binary_logloss: 0.677508\n",
      "[13]\tvalid_0's l1: 0.487504\tvalid_0's binary_logloss: 0.677646\n",
      "[14]\tvalid_0's l1: 0.487319\tvalid_0's binary_logloss: 0.67724\n",
      "Early stopping, best iteration is:\n",
      "[9]\tvalid_0's l1: 0.488975\tvalid_0's binary_logloss: 0.676579\n",
      "[1]\tvalid_0's l1: 0.500027\tvalid_0's binary_logloss: 0.693799\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.499582\tvalid_0's binary_logloss: 0.693072\n",
      "[3]\tvalid_0's l1: 0.499091\tvalid_0's binary_logloss: 0.692253\n",
      "[4]\tvalid_0's l1: 0.499462\tvalid_0's binary_logloss: 0.69349\n",
      "[5]\tvalid_0's l1: 0.499319\tvalid_0's binary_logloss: 0.693893\n",
      "[6]\tvalid_0's l1: 0.498794\tvalid_0's binary_logloss: 0.693739\n",
      "[7]\tvalid_0's l1: 0.498049\tvalid_0's binary_logloss: 0.693254\n",
      "[8]\tvalid_0's l1: 0.497694\tvalid_0's binary_logloss: 0.693611\n",
      "Early stopping, best iteration is:\n",
      "[3]\tvalid_0's l1: 0.499091\tvalid_0's binary_logloss: 0.692253\n",
      "[1]\tvalid_0's l1: 0.50024\tvalid_0's binary_logloss: 0.694202\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.49866\tvalid_0's binary_logloss: 0.6916\n",
      "[3]\tvalid_0's l1: 0.497466\tvalid_0's binary_logloss: 0.690118\n",
      "[4]\tvalid_0's l1: 0.496775\tvalid_0's binary_logloss: 0.689527\n",
      "[5]\tvalid_0's l1: 0.496603\tvalid_0's binary_logloss: 0.690456\n",
      "[6]\tvalid_0's l1: 0.49607\tvalid_0's binary_logloss: 0.69082\n",
      "[7]\tvalid_0's l1: 0.495731\tvalid_0's binary_logloss: 0.691305\n",
      "[8]\tvalid_0's l1: 0.494276\tvalid_0's binary_logloss: 0.690151\n",
      "[9]\tvalid_0's l1: 0.49358\tvalid_0's binary_logloss: 0.690439\n",
      "Early stopping, best iteration is:\n",
      "[4]\tvalid_0's l1: 0.496775\tvalid_0's binary_logloss: 0.689527\n",
      "[1]\tvalid_0's l1: 0.500739\tvalid_0's binary_logloss: 0.695375\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.500217\tvalid_0's binary_logloss: 0.694566\n",
      "[3]\tvalid_0's l1: 0.499029\tvalid_0's binary_logloss: 0.692881\n",
      "[4]\tvalid_0's l1: 0.498693\tvalid_0's binary_logloss: 0.692418\n",
      "[5]\tvalid_0's l1: 0.498086\tvalid_0's binary_logloss: 0.692412\n",
      "[6]\tvalid_0's l1: 0.497232\tvalid_0's binary_logloss: 0.691046\n",
      "[7]\tvalid_0's l1: 0.497169\tvalid_0's binary_logloss: 0.69228\n",
      "[8]\tvalid_0's l1: 0.495819\tvalid_0's binary_logloss: 0.690597\n",
      "[9]\tvalid_0's l1: 0.494719\tvalid_0's binary_logloss: 0.690008\n",
      "[10]\tvalid_0's l1: 0.494339\tvalid_0's binary_logloss: 0.690112\n",
      "[11]\tvalid_0's l1: 0.49345\tvalid_0's binary_logloss: 0.690136\n",
      "[12]\tvalid_0's l1: 0.493034\tvalid_0's binary_logloss: 0.690399\n",
      "[13]\tvalid_0's l1: 0.492896\tvalid_0's binary_logloss: 0.69148\n",
      "[14]\tvalid_0's l1: 0.492481\tvalid_0's binary_logloss: 0.691332\n",
      "Early stopping, best iteration is:\n",
      "[9]\tvalid_0's l1: 0.494719\tvalid_0's binary_logloss: 0.690008\n",
      "[1]\tvalid_0's l1: 0.499683\tvalid_0's binary_logloss: 0.693595\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.498137\tvalid_0's binary_logloss: 0.691269\n",
      "[3]\tvalid_0's l1: 0.496383\tvalid_0's binary_logloss: 0.688867\n",
      "[4]\tvalid_0's l1: 0.495584\tvalid_0's binary_logloss: 0.688003\n",
      "[5]\tvalid_0's l1: 0.494702\tvalid_0's binary_logloss: 0.687454\n",
      "[6]\tvalid_0's l1: 0.49428\tvalid_0's binary_logloss: 0.687657\n",
      "[7]\tvalid_0's l1: 0.493633\tvalid_0's binary_logloss: 0.687194\n",
      "[8]\tvalid_0's l1: 0.492774\tvalid_0's binary_logloss: 0.687367\n",
      "[9]\tvalid_0's l1: 0.492631\tvalid_0's binary_logloss: 0.688723\n",
      "[10]\tvalid_0's l1: 0.492344\tvalid_0's binary_logloss: 0.689085\n",
      "[11]\tvalid_0's l1: 0.491101\tvalid_0's binary_logloss: 0.688175\n",
      "[12]\tvalid_0's l1: 0.490473\tvalid_0's binary_logloss: 0.689075\n",
      "Early stopping, best iteration is:\n",
      "[7]\tvalid_0's l1: 0.493633\tvalid_0's binary_logloss: 0.687194\n",
      "[1]\tvalid_0's l1: 0.49998\tvalid_0's binary_logloss: 0.693805\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.497834\tvalid_0's binary_logloss: 0.689777\n",
      "[3]\tvalid_0's l1: 0.496964\tvalid_0's binary_logloss: 0.68825\n",
      "[4]\tvalid_0's l1: 0.495562\tvalid_0's binary_logloss: 0.686079\n",
      "[5]\tvalid_0's l1: 0.493892\tvalid_0's binary_logloss: 0.683593\n",
      "[6]\tvalid_0's l1: 0.493337\tvalid_0's binary_logloss: 0.683126\n",
      "[7]\tvalid_0's l1: 0.491981\tvalid_0's binary_logloss: 0.681505\n",
      "[8]\tvalid_0's l1: 0.49051\tvalid_0's binary_logloss: 0.678823\n",
      "[9]\tvalid_0's l1: 0.488975\tvalid_0's binary_logloss: 0.676579\n",
      "[10]\tvalid_0's l1: 0.489269\tvalid_0's binary_logloss: 0.677711\n",
      "[11]\tvalid_0's l1: 0.488243\tvalid_0's binary_logloss: 0.676685\n",
      "[12]\tvalid_0's l1: 0.488331\tvalid_0's binary_logloss: 0.677508\n",
      "[13]\tvalid_0's l1: 0.487504\tvalid_0's binary_logloss: 0.677646\n",
      "[14]\tvalid_0's l1: 0.487319\tvalid_0's binary_logloss: 0.67724\n",
      "Early stopping, best iteration is:\n",
      "[9]\tvalid_0's l1: 0.488975\tvalid_0's binary_logloss: 0.676579\n",
      "[1]\tvalid_0's l1: 0.500027\tvalid_0's binary_logloss: 0.693799\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.499582\tvalid_0's binary_logloss: 0.693072\n",
      "[3]\tvalid_0's l1: 0.499091\tvalid_0's binary_logloss: 0.692253\n",
      "[4]\tvalid_0's l1: 0.499462\tvalid_0's binary_logloss: 0.69349\n",
      "[5]\tvalid_0's l1: 0.499319\tvalid_0's binary_logloss: 0.693893\n",
      "[6]\tvalid_0's l1: 0.498794\tvalid_0's binary_logloss: 0.693739\n",
      "[7]\tvalid_0's l1: 0.498049\tvalid_0's binary_logloss: 0.693254\n",
      "[8]\tvalid_0's l1: 0.497694\tvalid_0's binary_logloss: 0.693611\n",
      "Early stopping, best iteration is:\n",
      "[3]\tvalid_0's l1: 0.499091\tvalid_0's binary_logloss: 0.692253\n",
      "[1]\tvalid_0's l1: 0.50024\tvalid_0's binary_logloss: 0.694202\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.49866\tvalid_0's binary_logloss: 0.6916\n",
      "[3]\tvalid_0's l1: 0.497466\tvalid_0's binary_logloss: 0.690118\n",
      "[4]\tvalid_0's l1: 0.496775\tvalid_0's binary_logloss: 0.689527\n",
      "[5]\tvalid_0's l1: 0.496603\tvalid_0's binary_logloss: 0.690456\n",
      "[6]\tvalid_0's l1: 0.49607\tvalid_0's binary_logloss: 0.69082\n",
      "[7]\tvalid_0's l1: 0.495731\tvalid_0's binary_logloss: 0.691305\n",
      "[8]\tvalid_0's l1: 0.494276\tvalid_0's binary_logloss: 0.690151\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[9]\tvalid_0's l1: 0.49358\tvalid_0's binary_logloss: 0.690439\n",
      "Early stopping, best iteration is:\n",
      "[4]\tvalid_0's l1: 0.496775\tvalid_0's binary_logloss: 0.689527\n",
      "[1]\tvalid_0's l1: 0.501222\tvalid_0's binary_logloss: 0.696246\n",
      "Training until validation scores don't improve for 5 rounds.\n",
      "[2]\tvalid_0's l1: 0.501065\tvalid_0's binary_logloss: 0.696001\n",
      "[3]\tvalid_0's l1: 0.500901\tvalid_0's binary_logloss: 0.695832\n",
      "[4]\tvalid_0's l1: 0.500713\tvalid_0's binary_logloss: 0.695632\n",
      "[5]\tvalid_0's l1: 0.500073\tvalid_0's binary_logloss: 0.694254\n",
      "[6]\tvalid_0's l1: 0.500044\tvalid_0's binary_logloss: 0.694378\n",
      "[7]\tvalid_0's l1: 0.49945\tvalid_0's binary_logloss: 0.693408\n",
      "[8]\tvalid_0's l1: 0.49884\tvalid_0's binary_logloss: 0.692289\n",
      "[9]\tvalid_0's l1: 0.498806\tvalid_0's binary_logloss: 0.6924\n",
      "[10]\tvalid_0's l1: 0.498585\tvalid_0's binary_logloss: 0.692036\n",
      "[11]\tvalid_0's l1: 0.497875\tvalid_0's binary_logloss: 0.690902\n",
      "[12]\tvalid_0's l1: 0.497871\tvalid_0's binary_logloss: 0.691108\n",
      "[13]\tvalid_0's l1: 0.496938\tvalid_0's binary_logloss: 0.689374\n",
      "[14]\tvalid_0's l1: 0.496171\tvalid_0's binary_logloss: 0.68838\n",
      "[15]\tvalid_0's l1: 0.495463\tvalid_0's binary_logloss: 0.687121\n",
      "[16]\tvalid_0's l1: 0.495139\tvalid_0's binary_logloss: 0.686645\n",
      "[17]\tvalid_0's l1: 0.495049\tvalid_0's binary_logloss: 0.68661\n",
      "[18]\tvalid_0's l1: 0.49438\tvalid_0's binary_logloss: 0.685441\n",
      "[19]\tvalid_0's l1: 0.49384\tvalid_0's binary_logloss: 0.684859\n",
      "[20]\tvalid_0's l1: 0.493578\tvalid_0's binary_logloss: 0.684779\n",
      "[21]\tvalid_0's l1: 0.49354\tvalid_0's binary_logloss: 0.68469\n",
      "[22]\tvalid_0's l1: 0.493195\tvalid_0's binary_logloss: 0.684477\n",
      "[23]\tvalid_0's l1: 0.492733\tvalid_0's binary_logloss: 0.683991\n",
      "[24]\tvalid_0's l1: 0.492208\tvalid_0's binary_logloss: 0.683399\n",
      "[25]\tvalid_0's l1: 0.492117\tvalid_0's binary_logloss: 0.683279\n",
      "[26]\tvalid_0's l1: 0.4916\tvalid_0's binary_logloss: 0.682466\n",
      "[27]\tvalid_0's l1: 0.491175\tvalid_0's binary_logloss: 0.682255\n",
      "[28]\tvalid_0's l1: 0.490931\tvalid_0's binary_logloss: 0.6823\n",
      "[29]\tvalid_0's l1: 0.490516\tvalid_0's binary_logloss: 0.681463\n",
      "[30]\tvalid_0's l1: 0.489961\tvalid_0's binary_logloss: 0.680666\n",
      "[31]\tvalid_0's l1: 0.489467\tvalid_0's binary_logloss: 0.680398\n",
      "[32]\tvalid_0's l1: 0.489019\tvalid_0's binary_logloss: 0.679576\n",
      "[33]\tvalid_0's l1: 0.488512\tvalid_0's binary_logloss: 0.679339\n",
      "[34]\tvalid_0's l1: 0.48851\tvalid_0's binary_logloss: 0.67971\n",
      "[35]\tvalid_0's l1: 0.488423\tvalid_0's binary_logloss: 0.679632\n",
      "[36]\tvalid_0's l1: 0.488359\tvalid_0's binary_logloss: 0.679399\n",
      "[37]\tvalid_0's l1: 0.488117\tvalid_0's binary_logloss: 0.67917\n",
      "[38]\tvalid_0's l1: 0.487639\tvalid_0's binary_logloss: 0.678965\n",
      "[39]\tvalid_0's l1: 0.487203\tvalid_0's binary_logloss: 0.67816\n",
      "[40]\tvalid_0's l1: 0.486783\tvalid_0's binary_logloss: 0.677607\n",
      "[41]\tvalid_0's l1: 0.486463\tvalid_0's binary_logloss: 0.677643\n",
      "[42]\tvalid_0's l1: 0.486404\tvalid_0's binary_logloss: 0.677458\n",
      "[43]\tvalid_0's l1: 0.485988\tvalid_0's binary_logloss: 0.67706\n",
      "[44]\tvalid_0's l1: 0.48564\tvalid_0's binary_logloss: 0.67716\n",
      "[45]\tvalid_0's l1: 0.485343\tvalid_0's binary_logloss: 0.677286\n",
      "[46]\tvalid_0's l1: 0.484886\tvalid_0's binary_logloss: 0.676437\n",
      "[47]\tvalid_0's l1: 0.484703\tvalid_0's binary_logloss: 0.676285\n",
      "[48]\tvalid_0's l1: 0.484415\tvalid_0's binary_logloss: 0.676179\n",
      "[49]\tvalid_0's l1: 0.484361\tvalid_0's binary_logloss: 0.676014\n",
      "[50]\tvalid_0's l1: 0.484289\tvalid_0's binary_logloss: 0.675983\n",
      "[51]\tvalid_0's l1: 0.483852\tvalid_0's binary_logloss: 0.675209\n",
      "[52]\tvalid_0's l1: 0.483499\tvalid_0's binary_logloss: 0.674753\n",
      "[53]\tvalid_0's l1: 0.4827\tvalid_0's binary_logloss: 0.673902\n",
      "[54]\tvalid_0's l1: 0.482552\tvalid_0's binary_logloss: 0.674148\n",
      "[55]\tvalid_0's l1: 0.482503\tvalid_0's binary_logloss: 0.674018\n",
      "[56]\tvalid_0's l1: 0.482371\tvalid_0's binary_logloss: 0.673975\n",
      "[57]\tvalid_0's l1: 0.481928\tvalid_0's binary_logloss: 0.673641\n",
      "[58]\tvalid_0's l1: 0.48177\tvalid_0's binary_logloss: 0.674286\n",
      "[59]\tvalid_0's l1: 0.481694\tvalid_0's binary_logloss: 0.67427\n",
      "[60]\tvalid_0's l1: 0.481601\tvalid_0's binary_logloss: 0.67485\n",
      "[61]\tvalid_0's l1: 0.48149\tvalid_0's binary_logloss: 0.674731\n",
      "[62]\tvalid_0's l1: 0.481404\tvalid_0's binary_logloss: 0.675227\n",
      "Early stopping, best iteration is:\n",
      "[57]\tvalid_0's l1: 0.481928\tvalid_0's binary_logloss: 0.673641\n",
      "search complete!!!\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Parallel(n_jobs=1)]: Done 270 out of 270 | elapsed:   32.0s finished\n"
     ]
    }
   ],
   "source": [
    "# sklearn接口形式\n",
    "import lightgbm as lgb\n",
    "import seaborn as sns\n",
    "print('version', lgb.__version__)\n",
    "\n",
    "# ## 导入LightGBM模型\n",
    "from lightgbm.sklearn import LGBMClassifier\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "\n",
    "# 搜索参数\n",
    "# params = {\n",
    "#     'boosting_type': ['gbdt', 'dart'],  # 设置提升类型\n",
    "#     'num_leaves': [31, 50, 100],  # 叶子节点数\n",
    "#     'max_depth': [3, 4, 5],\n",
    "#     'n_estimators': [100, 300, 500, 1000],\n",
    "#     'learning_rate': [0.01, 0.05, 0.1],  # 学习速率\n",
    "#     'feature_fraction': [0.8, 0.9],  # 建树的特征选择比例\n",
    "#     'bagging_fraction': [0.8, 0.9],  # 建树的样本采样比例\n",
    "#     'bagging_freq': [5, 8],  # k 意味着每 k 次迭代执行bagging\n",
    "# }\n",
    "# 由于时间过长，减少搜索参数\n",
    "params = {\n",
    "    'num_leaves': [31, 50, 100],  # 叶子节点数\n",
    "    'max_depth': [3, 5, 8],\n",
    "    'n_estimators': [100, 500, 1000],\n",
    "    'learning_rate': [0.01, 0.05],  # 学习速率\n",
    "}\n",
    "\n",
    "# ## 定义 LightGBM 模型，verbose <0 显示致命的, =0 显示错误 (警告), >0 显示信息 \n",
    "lgb_class = LGBMClassifier(objective='binary', verbose=1)\n",
    "clf = GridSearchCV(lgb_class, params, scoring='roc_auc', cv=5, n_jobs=1, verbose=1)\n",
    "\n",
    "# # 在训练集上训练LightGBM模型\n",
    "clf.fit(x_train, y_train, eval_set=[(x_eval, y_eval)], eval_metric='l1', early_stopping_rounds=5)\n",
    "print('search complete!!!')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.4615526454290277\n",
      "{'learning_rate': 0.05, 'max_depth': 3, 'n_estimators': 100, 'num_leaves': 31}\n",
      "The train accuracy of the LGB is: 0.66693354683747\n",
      "The eval accuracy of the LGB is: 0.5655172413793104\n",
      "The test accuracy of the LGB is: 0.5655172413793104\n",
      "The confusion matrix result:\n",
      " [[68 60]\n",
      " [66 96]]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.6/site-packages/sklearn/preprocessing/label.py:151: DeprecationWarning: The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use `array.size > 0` to check that an array is not empty.\n",
      "  if diff:\n",
      "/opt/conda/lib/python3.6/site-packages/sklearn/preprocessing/label.py:151: DeprecationWarning: The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use `array.size > 0` to check that an array is not empty.\n",
      "  if diff:\n",
      "/opt/conda/lib/python3.6/site-packages/sklearn/preprocessing/label.py:151: DeprecationWarning: The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use `array.size > 0` to check that an array is not empty.\n",
      "  if diff:\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(clf.best_score_)    #查看最佳分数(此处为f1_score)\n",
    "print(clf.best_params_)   #查看最佳参数\n",
    "clf = clf.best_estimator_  # 获取最佳模型\n",
    "\n",
    "## 在训练集和测试集上分布利用训练好的模型进行预测\n",
    "train_predict = clf.predict(x_train)\n",
    "eval_predict = clf.predict(x_eval)\n",
    "test_predict = clf.predict(x_test)\n",
    "\n",
    "from sklearn import metrics\n",
    "\n",
    "## 利用accuracy（准确度）【预测正确的样本数目占总预测样本数目的比例】评估模型效果\n",
    "print('The train accuracy of the LGB is:',metrics.accuracy_score(y_train,train_predict))\n",
    "print('The eval accuracy of the LGB is:',metrics.accuracy_score(y_eval,eval_predict))\n",
    "print('The test accuracy of the LGB is:',metrics.accuracy_score(y_test,test_predict))\n",
    "\n",
    "## 查看混淆矩阵 (预测值和真实值的各类情况统计矩阵)\n",
    "confusion_matrix_result = metrics.confusion_matrix(test_predict,y_test)\n",
    "print('The confusion matrix result:\\n',confusion_matrix_result)\n",
    "\n",
    "# 利用热力图对于结果进行可视化\n",
    "plt.figure(figsize=(8, 6))\n",
    "sns.heatmap(confusion_matrix_result, annot=True, cmap='Blues')\n",
    "plt.xlabel('Predicted labels')\n",
    "plt.ylabel('True labels')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5.4 模型保存和调用"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['lgb_clf_stock.pkl']"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.externals import joblib\n",
    "# 模型存储\n",
    "joblib.dump(clf, 'lgb_clf_stock.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The accuracy_score of prediction is: 0.5551724137931034\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.6/site-packages/sklearn/preprocessing/label.py:151: DeprecationWarning: The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use `array.size > 0` to check that an array is not empty.\n",
      "  if diff:\n"
     ]
    }
   ],
   "source": [
    "from sklearn.externals import joblib\n",
    "\n",
    "# 模型加载 (todo：如果不运行之前的训练流程，直接加载模型无法使用，暂不确定原因)\n",
    "clf = joblib.load('lgb_clf_stock.pkl')\n",
    "\n",
    "# 模型预测\n",
    "y_pred = clf.predict(x_test, num_iteration=clf.best_iteration_)\n",
    "\n",
    "# 模型评估\n",
    "print('The accuracy_score of prediction is:', metrics.accuracy_score(y_test, y_pred))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5.5 特征重要性评估"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>features</th>\n",
       "      <th>importance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>MAWVAD</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>BR</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>sales_to_price_ratio</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>ATR14</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>TVSTD6</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>turnover_volatility</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>VMACD</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>circulating_market_cap</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>TVSTD20</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>cash_flow_to_price_ratio</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>ATR6</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>DAVOL10</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>DAVOL5</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>VDEA</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>ARBR</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>VEMA5</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>low</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>VDIFF</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>money_flow_20</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>DAVOL20</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>volume</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>interest_carry_current_liability</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>open</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>np_parent_company_owners_ttm</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>high</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>VEMA26</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>financial_assets</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>market_cap</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>VEMA12</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>retained_earnings</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>asset_impairment_loss_ttm</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>net_profit_ttm</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>total_profit_ttm</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>net_invest_cash_flow_ttm</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>EBITDA</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>total_operating_revenue_ttm</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>TVMA6</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>goods_sale_and_service_render_cash_ttm</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>EBIT</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>operating_profit_ttm</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>net_working_capital</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>financial_liability</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>operating_assets</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>net_debt</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>non_operating_net_profit_ttm</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>PSY</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>total_operating_cost_ttm</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>OperateNetIncome</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>net_operate_cash_flow_ttm</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>net_interest_expense</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>non_recurring_gain_loss</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>TVMA20</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>AR</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>sale_expense_ttm</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>close</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>financial_expense_ttm</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>gross_profit_ttm</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>administration_expense_ttm</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>operating_liability</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>operating_revenue_ttm</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>66 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  features  importance\n",
       "42                                  MAWVAD          24\n",
       "38                                      BR          24\n",
       "59                    sales_to_price_ratio          20\n",
       "26                                   ATR14          18\n",
       "55                                  TVSTD6          17\n",
       "13                     turnover_volatility          15\n",
       "63                                   VMACD          15\n",
       "7                   circulating_market_cap          13\n",
       "58                                 TVSTD20          12\n",
       "14                cash_flow_to_price_ratio          12\n",
       "53                                    ATR6          10\n",
       "30                                 DAVOL10          10\n",
       "6                                   DAVOL5          10\n",
       "12                                    VDEA           9\n",
       "24                                    ARBR           9\n",
       "37                                   VEMA5           8\n",
       "3                                      low           6\n",
       "41                                   VDIFF           6\n",
       "22                           money_flow_20           5\n",
       "64                                 DAVOL20           5\n",
       "4                                   volume           5\n",
       "56        interest_carry_current_liability           4\n",
       "0                                     open           4\n",
       "44            np_parent_company_owners_ttm           3\n",
       "2                                     high           3\n",
       "50                                  VEMA26           3\n",
       "9                         financial_assets           2\n",
       "60                              market_cap           1\n",
       "61                                  VEMA12           1\n",
       "17                       retained_earnings           1\n",
       "..                                     ...         ...\n",
       "49               asset_impairment_loss_ttm           0\n",
       "47                          net_profit_ttm           0\n",
       "54                        total_profit_ttm           0\n",
       "51                net_invest_cash_flow_ttm           0\n",
       "62                                  EBITDA           0\n",
       "52             total_operating_revenue_ttm           0\n",
       "57                                   TVMA6           0\n",
       "33  goods_sale_and_service_render_cash_ttm           0\n",
       "43                                    EBIT           0\n",
       "40                    operating_profit_ttm           0\n",
       "8                      net_working_capital           0\n",
       "10                     financial_liability           0\n",
       "11                        operating_assets           0\n",
       "15                                net_debt           0\n",
       "16            non_operating_net_profit_ttm           0\n",
       "19                                     PSY           0\n",
       "20                total_operating_cost_ttm           0\n",
       "21                        OperateNetIncome           0\n",
       "23               net_operate_cash_flow_ttm           0\n",
       "25                    net_interest_expense           0\n",
       "27                 non_recurring_gain_loss           0\n",
       "28                                  TVMA20           0\n",
       "29                                      AR           0\n",
       "32                        sale_expense_ttm           0\n",
       "1                                    close           0\n",
       "34                   financial_expense_ttm           0\n",
       "35                        gross_profit_ttm           0\n",
       "36              administration_expense_ttm           0\n",
       "39                     operating_liability           0\n",
       "65                   operating_revenue_ttm           0\n",
       "\n",
       "[66 rows x 2 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 特征重要度\n",
    "#print('Feature importances:', list(clf.feature_importances_))\n",
    "\n",
    "# 根据重要性，进行特征筛选。输出2列，因子名和重要性\n",
    "factor_weight = pd.DataFrame({'features':list(ft_names),\n",
    "                             'importance':clf.feature_importances_}).sort_values(\n",
    "    #这里根据重要程度降序排列，一遍遍找到重要性最高的特征\n",
    "    by='importance', ascending = False)\n",
    "#检查结果，可以看到重要性和决策树略有差异\n",
    "factor_weight"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 绘制特征重要性图像\n",
    "plt.title('Feature Importance')\n",
    "# 特征数量 和 特征重要性\n",
    "plt.bar(range(factor_weight.shape[0]), factor_weight['importance'], color='blue', align='center')\n",
    "# 横轴特征名\n",
    "plt.xticks(range(factor_weight.shape[0]), factor_weight['features'], rotation=90)\n",
    "           # fontdict={'color':'red', 'size':16})\n",
    "plt.xlim([-1, factor_weight.shape[0]])\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 6. TopKDropN选股择时策略\n",
    "原理：   \n",
    "1. 基于模型对股票池股票预测“涨”的概率值进行排序，选择topK个股票进行买入\n",
    "2. 基于模型对持仓股票预测“跌”的概率值进行排序，清仓N支股票"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ft_len 66\n",
      "val_all shape: (8, 66)\n"
     ]
    }
   ],
   "source": [
    "# 从之前测试数据注，每个股票抽取第一天的数据，模拟每天交易过程的选股\n",
    "import numpy as np\n",
    "stk_lst, val_lst = [], []\n",
    "ft_len = len(ft_names)\n",
    "print('ft_len', ft_len)\n",
    "\n",
    "for key, val in df_test_dict.items():\n",
    "    # 一维转二维\n",
    "    # del df_all['lab']，这种方法会影响df_dict里的数据，后续df_dict里的lab列无法获取\n",
    "    x = val.loc[:, val.columns != 'lab']\n",
    "    val_array = x.iloc[0, :].values.reshape(1, -1)\n",
    "    if val_array.shape[1] != ft_len:\n",
    "       continue\n",
    "    stk_lst.append(key)\n",
    "    val_lst.append(val_array)\n",
    "    \n",
    "val_all = np.concatenate(val_lst, axis=0)\n",
    "print('val_all shape:', val_all.shape)\n",
    "\n",
    "# 如下预测忘加标准化处理，请自行加入\n",
    "#from sklearn import preprocessing\n",
    "#val_all=preprocessing.StandardScaler()\n",
    "#val_all=scaler.fit_transform(val_all)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test_probs [[0.6071636758820642 0.39283632411793573]\n",
      " [0.662436919053922 0.337563080946078]\n",
      " [0.5698603754419066 0.4301396245580934]\n",
      " [0.5661390845594774 0.4338609154405227]\n",
      " [0.6975304160401822 0.3024695839598178]\n",
      " [0.6817010047942658 0.3182989952057343]\n",
      " [0.5031193464425533 0.4968806535574467]\n",
      " [0.7207876371284441 0.27921236287155593]]\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>stk</th>\n",
       "      <th>prob</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>000166.XSHE</td>\n",
       "      <td>0.496881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>000069.XSHE</td>\n",
       "      <td>0.433861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>000066.XSHE</td>\n",
       "      <td>0.430140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>000001.XSHE</td>\n",
       "      <td>0.392836</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>000002.XSHE</td>\n",
       "      <td>0.337563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>000157.XSHE</td>\n",
       "      <td>0.318299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>000100.XSHE</td>\n",
       "      <td>0.302470</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>000333.XSHE</td>\n",
       "      <td>0.279212</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           stk      prob\n",
       "6  000166.XSHE  0.496881\n",
       "3  000069.XSHE  0.433861\n",
       "2  000066.XSHE  0.430140\n",
       "0  000001.XSHE  0.392836\n",
       "1  000002.XSHE  0.337563\n",
       "5  000157.XSHE  0.318299\n",
       "4  000100.XSHE  0.302470\n",
       "7  000333.XSHE  0.279212"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "# 获取\n",
    "test_probs = clf.predict_proba(val_all)\n",
    "print('test_probs', test_probs)\n",
    "\n",
    "# 第一列是标签0的概率，第二列是标签1的概率\n",
    "data_dict = {'stk': stk_lst, 'prob': test_probs[:, 1]}\n",
    "df_pred = pd.DataFrame(data_dict, columns=data_dict.keys())\n",
    "df_pred.sort_values(by=\"prob\", inplace=True, ascending=False)  # inplace: 原地修改\n",
    "df_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6    000166.XSHE\n",
       "3    000069.XSHE\n",
       "2    000066.XSHE\n",
       "Name: stk, dtype: object"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 选择TOP3的股票\n",
    "df_pred['stk'][:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ori:\n",
      "            stk      prob\n",
      "7  000333.XSHE  0.720788\n",
      "4  000100.XSHE  0.697530\n",
      "5  000157.XSHE  0.681701\n",
      "1  000002.XSHE  0.662437\n",
      "0  000001.XSHE  0.607164\n",
      "2  000066.XSHE  0.569860\n",
      "3  000069.XSHE  0.566139\n",
      "6  000166.XSHE  0.503119\n",
      "dropN\n",
      " 7    000333.XSHE\n",
      "4    000100.XSHE\n",
      "5    000157.XSHE\n",
      "Name: stk, dtype: object\n"
     ]
    }
   ],
   "source": [
    "# 第一列是标签0的概率，第二列是标签1的概率\n",
    "data_dict = {'stk': stk_lst, 'prob': test_probs[:, 0]}\n",
    "df_pred = pd.DataFrame(data_dict, columns=data_dict.keys())\n",
    "df_pred.sort_values(by=\"prob\", inplace=True, ascending=False)  # inplace: 原地修改\n",
    "print('ori:\\n', df_pred)\n",
    "\n",
    "# 将持仓的top3做空\n",
    "print('dropN\\n', df_pred['stk'][:3])"
   ]
  }
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